Miracle-dz/UniFAR-FTUs huggingface dataset:
Posttraumatic stress disorder symptom trajectories in a 16‐month COVID‐19 pandemic period

Abstract COVID‐19 pandemic presents an unheralded opportunity to better understand trajectories of posttraumatic stress disorder (PTSD) symptoms across a prolonged period of social disruption and stress. We tracked PTSD symptoms among trauma‐exposed individuals in the United States and sought to identify population‐based variability in PTSD symptom trajectories and understand what, if any, early pandemic experiences predicted membership in one trajectory versus others. As part of a longitudinal study of U.S. residents during the pandemic, participants who reported at least one potentially traumatic experience in their lifetime (N = 1,206) at Wave 1 (April 2020) were included in the current study. PTSD symptoms were assessed using the PCL‐5 at four time points extending to July 2021. Latent growth mixture modeling was used to identify heterogeneous symptom trajectories. Trajectory membership was regressed on experiences from the early stage of the pandemic as measured using the Epidemic‐Pandemic Impacts Inventory in a model that controlled for variables with documented associations to PTSD trajectories, including age, sex, income, and trauma history. Four trajectories were identified, categorized as resilient (73.0%), recurring (13.3%), recovering (8.3%), and chronic (5.5%). Emotional and physical health problems and positive changes associated with the early phase of the pandemic were each significant predictors of trajectory membership over and above all other variables in the model. Predictors primarily differentiated the resilient trajectory from each of the other three trajectories. Distinct PTSD symptom trajectories during the COVID‐19 pandemic suggest a need for targeted efforts to help individuals at most risk for ongoing distress.
The Development of Symbolic Expressions for Fire Detection with Symbolic Classifier Using Sensor Fusion Data

Fire is usually detected with fire detection systems that are used to sense one or more products resulting from the fire such as smoke, heat, infrared, ultraviolet light radiation, or gas. Smoke detectors are mostly used in residential areas while fire alarm systems (heat, smoke, flame, and fire gas detectors) are used in commercial, industrial and municipal areas. However, in addition to smoke, heat, infrared, ultraviolet light radiation, or gas, other parameters could indicate a fire, such as air temperature, air pressure, and humidity, among others. Collecting these parameters requires the development of a sensor fusion system. However, with such a system, it is necessary to develop a simple system based on artificial intelligence (AI) that will be able to detect fire with high accuracy using the information collected from the sensor fusion system. The novelty of this paper is to show the procedure of how a simple AI system can be created in form of symbolic expression obtained with a genetic programming symbolic classifier (GPSC) algorithm and can be used as an additional tool to detect fire with high classification accuracy. Since the investigation is based on an initially imbalanced and publicly available dataset (high number of samples classified as 1-Fire Alarm and small number of samples 0-No Fire Alarm), the idea is to implement various balancing methods such as random undersampling/oversampling, Near Miss-1, ADASYN, SMOTE, and Borderline SMOTE. The obtained balanced datasets were used in GPSC with random hyperparameter search combined with 5-fold cross-validation to obtain symbolic expressions that could detect fire with high classification accuracy. For this investigation, the random hyperparameter search method and 5-fold cross-validation had to be developed. Each obtained symbolic expression was evaluated on train and test datasets to obtain mean and standard deviation values of accuracy (ACC), area under the receiver operating characteristic curve (AUC), precision, recall, and F1-score. Based on the conducted investigation, the highest classification metric values were achieved in the case of the dataset balanced with SMOTE method. The obtained values of ACC¯±SD(ACC), AUC¯±SD(ACU), Precision¯±SD(Precision), Recall¯±SD(Recall), and F1-score¯±SD(F1-score) are equal to 0.998±4.79×10−5, 0.998±4.79×10−5, 0.999±5.32×10−5, 0.998±4.26×10−5, and 0.998±4.796×10−5, respectively. The symbolic expression using which best values of classification metrics were achieved is shown, and the final evaluation was performed on the original dataset.
Adaptive compensation for infinite number of actuator failures with an application to flight control

In this paper, a new adaptive compensation control scheme is proposed for a class of nonlinear systems with unknown parameters and unknown actuator failures. The normal operation case and different failure cases of actuators are unified through a time‐varying model. By introducing a smooth function, an integrable auxiliary signal, and a bound estimation approach, the effect of failures is successfully compensated for, and the total number of failures is not restricted to be finite. It is shown that all closed‐loop signals are globally uniformly bounded, and the tracking error converges to zero asymptotically regardless of the possibly infinite number of actuator failures. An application to the longitudinal dynamic model of a twin otter aircraft is presented to illustrate the effectiveness of the proposed scheme. Copyright © 2015 John Wiley & Sons, Ltd.
Efficient Evolutionary Algorithm for solving Multiobjective Transportation Problem

This paper presents an efficient evolutionary algorithm for solving multi objectivetransportation problem MOTP. The proposed approach integrates the merits of both genetic algorithm(GA) and local search (LS), where it employs the concept of co-evolution and repair algorithm forhandling nonlinear constraints, also, it maintains a finite-sized archive of non-dominated solutions whichgets iteratively updated in the presence of new solutions based on the concept of e -dominance. The useof e -dominance also makes the algorithms practical by allowing a decision maker to control theresolution of the Pareto set approximation. To increase GAs’ problem solution power, local searchtechnique was implemented as neighborhood search engine where it intends to explore the less-crowdedarea in the current archive to possibly obtain more nondominated solutions.Finally, we report numerical results in order to establish the actual computational burden of the proposedalgorithm and to assess its performances with respect to classical approaches for solving MOTP.Key words. Multiobjective Transportation Problem, Genetic Algorithms, Local search.
Risk Factors for Carbapenem Resistant Gram Negative Bacteria (CR-GNB) Carriage Upon Admission to the Gastroenterology Department in a Tertiary First Class Hospital of China: Development and Assessment of a New Predictive Nomogram

Background With the increasing number of critically ill patients in the gastroenterology department (GED), infections associated with Carbapenem resistant gram-negative bacteria (CR-GNB) are of great concern in GED. As the turn-around time (TAT) for a positive screening culture result is slow, contact precaution and pre-emptive isolation, cohorting methods should be undertaken immediately on admission for high-risk patients. Accurate prediction tools for CR-GNB colonization in GED can help determine target populations upon admission. And thus, clinicians and nurses can implement preventive measures more timely and effectively. Objective The purpose of the current study was to develop and internally validate a CR-GNB carrier risk predictive nomogram for a Chinese population in GED. Methods Based on a training dataset of 400 GED patients collected between January 2020 and December 2021, we developed a model to predict CR-GNB carrier risk. A rectal swab was used to evaluate the patients’ CR-GNB colonization status microbiologically. We optimized features selection using the least absolute shrinkage and selection operator regression model (LASSO). In order to develop a predicting model, multivariable logistic regression analysis was then undertaken. Various aspects of the predicting model were evaluated, including discrimination, calibration, and clinical utility. We assessed internal validation using bootstrapping. Results The prediction nomogram includes the following predictors: Transfer from another hospital (Odds ratio [OR] 3.48), High Eastern Cooperative Oncology Group (ECOG) performance status (OR 2.61), Longterm in healthcare facility (OR 10.94), ICU admission history (OR 9.03), Blood stream infection history (OR 3.31), Liver cirrhosis (OR 4.05) and Carbapenem usage history within 3 month (OR 2.71). The model demonstrated good discrimination and good calibration. Conclusion With an estimate of individual risk using the nomogram developed in this study, clinicians and nurses can take more timely infection preventive measures on isolation, cohorting and medical interventions.
PetaKV: Building Efficient Key-Value Store for File System Metadata on Persistent Memory

Previous works proposed building file systems and organizing the metadata with KV stores because KV stores handle entries of various sizes efficiently and have excellent scalability. The emergence of the byte-addressable persistent memory (PM) enables metadata service to be faster than before by tailoring the KV store for the PM. However, existing PM-based KV stores cannot handle the workloads of file systems’ metadata well because simply depending on hash tables or trees cannot simultaneously provide fast file accessing and efficient directory traversing. In this paper, we exploit the insight of the metadata operations and propose the PetaKV, a KV store tailored for the metadata management of file systems on PM. PetaKV leverages dual hash indexing to achieve fast file put and get operations. Moreover, it cooperates with PM-tailored peta logs to collocate KV entries for each directory, thus supporting efficient directory scans. Our evaluation indicates PetaKV outperforms state-of-art tree-based KV stores on put, get and scan <inline-formula><tex-math notation="LaTeX">$2.5\times$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>2</mml:mn><mml:mo>. </mml:mo><mml:mn>5</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="zhou-ieq1-3232382.gif"/></alternatives></inline-formula>, <inline-formula><tex-math notation="LaTeX">$3.2\times$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>3</mml:mn><mml:mo>. </mml:mo><mml:mn>2</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="zhou-ieq2-3232382.gif"/></alternatives></inline-formula>, and <inline-formula><tex-math notation="LaTeX">$2.8\times$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>2</mml:mn><mml:mo>. </mml:mo><mml:mn>8</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="zhou-ieq3-3232382.gif"/></alternatives></inline-formula> on average, respectively. Moreover, the file system built with PetaKV achieves <inline-formula><tex-math notation="LaTeX">$1.2\times$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>1</mml:mn><mml:mo>. </mml:mo><mml:mn>2</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="zhou-ieq4-3232382.gif"/></alternatives></inline-formula> to <inline-formula><tex-math notation="LaTeX">$6.4\times$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>6</mml:mn><mml:mo>. </mml:mo><mml:mn>4</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="zhou-ieq5-3232382.gif"/></alternatives></inline-formula> speedup compared to those built with tree-based KV stores on the metadata operations.
Detection of an Undescribed Babesia sp. in Capybaras and Amblyomma Ticks in Central-Western Brazil

Simple Summary Capybaras are known hosts for various tick species, but there are limited data regarding the tick-borne pathogens they can carry. We assessed the presence of piroplasmids and Ehrlichia spp. in capybaras and their associated ticks in Goiás state, central-western Brazil. Neither capybaras nor ticks were positive for Ehrlichia spp. However, we detected an undescribed species of protozoan in both the capybaras and ticks. Further research is required for a formal delineation of this protozoan species, as well as to investigate the role of these ticks as vectors and the possible pathogenicity of this parasite to other animals, including horses. Abstract Capybaras (Hydrochoerus hydrochaeris) are the largest rodents on Earth. While capybaras are hosts for various tick species, there is limited information regarding the tick-borne pathogens they can carry. We investigated the presence of piroplasmids and Ehrlichia spp. in capybaras and their associated ticks in two peri-urban areas in Goiás state, central-western Brazil. Blood samples collected from 23 capybaras were used to investigate the presence of piroplasmids and Ehrlichia spp. in stained-blood smears and by PCR. Ticks collected from the capybaras were identified morphologically and also tested using PCR for the same pathogens. A total of 955 ticks were collected, including 822 (86.1%) Amblyomma sculptum, 132 (13.8%) Amblyomma dubitatum, and one (0.1%) unidentified larva of Amblyomma sp. Neither the capybaras nor ticks were positive for Ehrlichia spp. However, a stained-blood smear examination revealed the presence of ring-stage and pyriform-shaped merozoites in the erythrocytes of one (4.4%) capybara. In the same way, 47.8% (11/23) and 19.9% (36/181) of blood samples and ticks, respectively, were positive for piroplasmids in the PCR. We successfully sequenced a partial 18S rRNA gene fragment of four samples (two capybaras, one A. sculptum, and one A. dubitatum), and the phylogenetic reconstruction disclosed that the organism reported in the present study clusters within the genus Babesia. Further research is required for a formal delineation of this species (designated as Babesia sp. strain Capybara) and to investigate the hypothesis of A. dubitatum and A. sculptum ticks being vectors.
The Virus-Induced Transcription Factor SHE1 Interacts with and Regulates Expression of the Inhibitor of Virus Replication (IVR) in N Gene Tobacco

The transcription factor SHE1 was induced by tobacco mosaic virus (TMV) infection in tobacco cv. Samsun NN (SNN) and SHE1 inhibited TMV accumulation when expressed constitutively. To better understand the role of SHE1 in virus infection, transgenic SNN tobacco plants generated to over-express SHE1 (OEx-SHE1) or silence expression of SHE1 (si-SHE1) were infected with TMV. OEx-SHE1 affected the local lesion resistance response to TMV, whereas si-SHE1 did not. However, si-SHE1 allowed a slow systemic infection to occur in SNN tobacco. An inhibitor of virus replication (IVR) was known to reduce the accumulation of TMV in SNN tobacco. Analysis of SHE1 and IVR mRNA levels in OEx-SHE1 plants showed constitutive expression of both mRNAs, whereas both mRNAs were less expressed in si-SHE1 plants, even after TMV infection, indicating that SHE1 and IVR were associated with a common signaling pathway. SHE1 and IVR interacted with each other in four different assay systems. The yeast two-hybrid assay also delimited sequences required for the interaction of these two proteins to the SHE1 central 58-79% region and the IVR C-terminal 50% of the protein sequences. This suggests that SHE is a transcription factor involved in the induction of IVR and that IVR binds to SHE1 to regulate its own synthesis.
The Mediterranean Diet in Paediatric Gastrointestinal Disorders

The Mediterranean diet is considered one of the healthiest dietary patterns worldwide, thanks to a combination of foods rich mainly in antioxidants and anti-inflammatory nutrients. Many studies have demonstrated a strong relationship between the Mediterranean diet and some chronic gastrointestinal diseases. The aim of this narrative review was to analyse the role of the Mediterranean diet in several gastrointestinal diseases, so as to give a useful overview on its effectiveness in the prevention and management of these disorders.
Secure P2P Nonfragile Sampled-Data Controller Design for Nonlinear Networked System under Sensor Saturation and DoS Attack

The main purpose of this article is to solve secure peak-to-peak (P2P) nonfragile sampled-data controller design problem for nonlinear networked system under sensor saturation and DoS attack, where the considered nonlinear system is described by a T-S fuzzy model. According to the characteristics of DoS attack, a sampling scheme with two different sampling periods is introduced, and the corresponding maximum control update interval is also given based on the sampling periods and the characteristics of DoS attack. From this, we model the closed-loop system as sampled-data system in which the controller is nonfragile. Then, the P2P stability analysis criteria are established, where, for the sensor saturation, a new analysis condition of bounding region is proposed to ensure the measurement output satisfies a given constraint condition under the influence of disturbance, thereby avoiding the problem of sensor saturation. Furthermore, based on this, we give a secure P2P nonfragile sampled-data control scheme to guarantee that the sampled-data system meets the given control performance under the sensor saturation and DoS attack. Finally, an example is proposed to illustrate the advantages of the method.
Stratified Normalization LogitBoost for Two-Class Unbalanced Data Classification

The research on unbalanced data classification is a hot topic in recent years. LogitBoost algorithm is an adaptive algorithm that can get much higher prediction precision. But in the face of unbalanced data, this algorithm could produce a large minority class prediction error. In this article, we propose an improved LogitBoost algorithm named BLogitBoost, based on a stratified normalization method which normalizes within class sampling probability first, then normalizes between classes. The experiments on simulation data and empirical data show that the new algorithm can reduce the minority class prediction error significantly.
Analog of the minkowski inequality for the difference of two M-matrices ∗

We investigate the similarity between positive definite matrices and M-matrices. Some well-known in-equalities for positive definite matrices are shown to be true for M-matrices. Main results are analogs of the Minkowski, Bergstrom and Fan inequalities for the difference of two M-matrices. Let A B be M-matrices of order n. If A−B is an inverse M-matrix, then and where A(i)B(i) denote the principal submatrices obtained by deleting the ith row and column, and more generally for k=1,2,…n, where A (k) B (k) denote the principal submatrices obtained by deleting the first k rows and columns. For positive definite matrices A B, where A − B is a positive definite matrix, the above inequalities are due to Minkowski, Bergstrom and Fan respectively.
Wideband Monopole Eight-Element MIMO Antenna for 5G Mobile Terminal

An eight-element wideband multiple-input multiple-output (MIMO) antenna for the fifth-generation (5G) mobile terminal is proposed. The antenna elements are placed along both long side edges of the mobile terminal with a profile of 6 mm. The proposed monopole-inspired antenna element shows a good impedance match, isolation, and diversity parameter across a very wide bandwidth of 78 % (3.2-7.3 GHz), and it can cover the 5G NR n77/n78/n79/n96, LTE 46, and WLAN 5 GHz bands. The result shows that the MIMO antenna can offer inter-element isolation better than 12 dB, envelope correlation coefficient (ECC) below 0.069, and a peak channel capacity of 42.7 bps/Hz across the desired 5G bands. The specific absorption rate (SAR) analysis of the proposed MIMO antenna with a human head has exhibited SAR levels (0.41 W/Kg and 0.33 W/Kg at two resonating frequencies 3.9 GHz and 5.8 GHz, respectively) much lower than the Federal Communications Commission (FCC) permissible limit (1.6 W/Kg over 1 gram tissue).
How does density of the inner mitochondrial membrane influence mitochondrial performance?

Our current understanding of variation in mitochondrial performance is incomplete. The production of ATP via oxidative phosphorylation is dependent, in part, upon the structure of the inner mitochondrial membrane. Morphology of the inner membrane is crucial for the formation of the proton gradient across the inner membrane and, therefore, ATP synthesis. The inner mitochondrial membrane is dynamic, changing shape and surface area. These changes alter density (amount per volume) of the inner mitochondrial membrane within the confined space of the mitochondrion. Because the number of electron transport system proteins within the inner mitochondrial membrane changes with inner mitochondrial membrane area, a change in the amount of inner membrane alters the capacity for ATP production within the organelle. This review outlines the evidence that the association between ATP synthases, inner mitochondrial membrane density, and mitochondrial density (number of mitochondria per cell), impact ATP production by mitochondria. Further, we consider possible constraints on the capacity of mitochondria to produce ATP by increasing inner mitochondrial membrane density.
The Photobiomodulation of MAO-A Affects the Contractile Activity of Smooth Muscle Gastric Tissues

Nowadays, the utilized electromagnetic radiation (ER) in modalities such as photobiomodulation (PBM) finds broader applications in medical practice due to the promising results suggested by numerous reports. To date, the published data do not allow for the in-depth elucidation of the molecular mechanisms through which ER impacts the human organism. Furthermore, there is a total lack of evidence justifying the relation between the enzymatic activity of monoamine oxidase A (MAO-A) and the effect of 5-hydroxytryptamine (5-HT) on the spontaneous contractile activity of smooth muscle gastric tissues exposed to various light sources. We found that exposure of these tissues to lamps, emitting light with wavelengths of 254 nm and 350 nm, lasers, emitting light with 532 nm and 808 nm, and light-emitting diodes (LEDs) with ER at a wavelength of 660 nm, increased the 5-HT effect on the contractility. On the other hand, LEDs at 365 nm and 470 nm reduced it. The analysis of MAO-A enzymatic activity after exposure to the employed light emitters endorsed these findings. Furthermore, MAOA gene expression studies confirmed the possibility of its optogenetic regulation. Therefore, we concluded that the utilized emitters could alternate the functions of significant neuromediators by modulating the activity and gene transcription levels of enzymes that degrade them. Our investigations will help to disclose the selective conditions upon which PBM can effectively treat gastrointestinal and neurological disorders.
Okishio, Nobuo, A Theory of Reproduction (In Japanese)

Allecation models, such as consumer demand systems, typically imply a degenerate error structure. The usual approach in estimation is to delete one equation, and to appeal to the results of Barten (1969), for example, that parameter estimates are invariant to the equation deleted. However such proofs of invariance are not straightforward. This paper demonstrates that such systems are observationally equivalent to structures common in the simultaneous equations literature, for which invariance is obvious, and hence provides a more transparent demonstration of conditions for invariance.