Miracle-dz/UniFAR-FTUs huggingface dataset:
Association between Suicidal Behaviors in Adolescence and Negative Emotions, the Level of Stress, Stress Coping Strategies and the Quality of Sleep

Suicidal behaviors in adolescents stem from complex processes deeply rooted in various spheres of life and functioning. The study was aimed at assessing the relationship between selected negative emotions, the quality of sleep, the level of perceived stress as well as stress coping strategies and suicidal ideation and attempts among high school students. The examined group consisted of adolescents aged 16–18 recruited by social-media groups in Poland. The study was based on a diagnostic survey with the application of CAWI method. The other research tools applied in the study included: Hospital Anxiety and Depression Scale—Modified, Perceived Stress Scale-10, How do you cope? —Questionnaire, Athens Insomnia Scale as well as the authors’ own questionnaire on suicidal ideation and suicide attempts. Anxiety, depression, aggression and insomnia as well as a high level of stress were statistically more common in girls than in boys (p < 0.001). The high level of negative emotions and insomnia, in turn, increased the risk of suicidal ideation (OR = 3.59, 95% CI: 2.13–6.06 and OR = 2.35, 95% CI: 1.60–3.46), as well as suicide attempts (OR = 6.29, 95% CI: 2.93–14.80 and OR = 3.29, 95% CI: 2.07–5.35). Additionally, high level of stress was associated with more than twice larger odds of suicidal ideation (OR = 2.26, 95% CI: 1.13–4.63). Significantly higher prevalence of suicidal ideation (p = 0.017) and suicide attempts (p = 0.016) was observed in girls. A high level of negative emotions and stress accompanied by a low quality of sleep are factors predisposing people to suicidal ideation and attempted suicide.
Silicon nanowires for multisensing applications

Detection and quantification of very small amounts of biological species become necessary to allow an early detection of biothreats. Currently, fluorescence detection and colorimetry are the most frequently used techniques. Although very sensitive, the necessary labelling step of the biotargets can alter their recognition properties and these methods have a low potential for integration. This explains the constant effort of research on label-free detection methods. Onedimensional nanostructures, such as silicon nanowires, have emerged as good candidates for ultra-sensitive electrical detection of biological species. A silicon nanowire can operate as the channel of a field-effect transistor whose conductance is modulated by the change of charge of its surface due to the binding of biological species. A top-down fabrication process of silicon nanowire field effect transistors was developed on SOI and the influence of several physico-chemical parameters such as environmental electrostatic charges, light, buffer salinity and flow rate was evaluated. A change of the conductance of the Si nanowire according to the pH of the solution was demonstrated. Si nanowires were also tested as biosensors and allowed us to a better understanding of the involved phenomena. Complementary measurements are currently under progress.
Cotton Fiber Quality Estimation Based on Machine Learning Using Time Series UAV Remote Sensing Data

As an important factor determining the competitiveness of raw cotton, cotton fiber quality has received more and more attention. The results of traditional detection methods are accurate, but the sampling cost is high and has a hysteresis, which makes it difficult to measure cotton fiber quality parameters in real time and at a large scale. The purpose of this study is to use time-series UAV (Unmanned Aerial Vehicle) multispectral and RGB remote sensing images combined with machine learning to model four main quality indicators of cotton fibers. A deep learning algorithm is used to identify and extract cotton boll pixels in remote sensing images and improve the accuracy of quantitative extraction of spectral features. In order to simplify the input parameters of the model, the stepwise sensitivity analysis method is used to eliminate redundant variables and obtain the optimal input feature set. The results of this study show that the R2 of the prediction model established by a neural network is improved by 29.67% compared with the model established by linear regression. When the spectral index is calculated after removing the soil pixels used for prediction, R2 is improved by 4.01% compared with the ordinary method. The prediction model can well predict the average length, uniformity index, and micronaire value of the upper half. R2 is 0.8250, 0.8014, and 0.7722, respectively. This study provides a method to predict the cotton fiber quality in a large area without manual sampling, which provides a new idea for variety breeding and commercial decision-making in the cotton industry.
Local linearization stability

It is shown that Einstein’s equations are always linearization stable around any finite region of space‐time. Let (Ω,g0ab ) be any region of space‐time, admitting a compact Cauchy surface with nonempty smooth boundary, and with g0ab a sufficiently smooth solution of the vacuum Einstein equation. It is shown that for any solution g1ab of the linearized equation and any open region U⊆Ω, there exists a smooth one‐parameter family gλab of solutions on U such that (gλab‖λ=0 =g0ab ) ‖U and ((d/dλ)gλab =g1ab )‖U. By using a result of Choquet‐Bruhat and York [The Cauchy Problem, General Relativity and Gravitation, edited by A. Held (Plenum, New York, 1980), Vol. 1] asserting the smoothness of the map that sends initial data into solutions of Einstein’s evolution equations the proof of the above theorem is reduced to the proof of a similar theorem for Einstein’s constraint equations. The proof of this latter theorem involves the use of the implicit function theorem in Hilbert spaces. This local result on lineariza.
A time-frequency approach to ensuring stability of machining by turning

This paper reports a new approach to ensuring the stability of the turning process, which is based on the frequency-time characteristics of the technological machining system (TMS). The approach uses a mathematical model of the turning process as a single-mass system with one degree of freedom, taking into account negative feedback on the normal coordinate and positive feedback with a delay in cutting depth. A new criterion for the stability of the cutting process as a system with a delay in positive feedback is proposed, based on the analysis of frequency characteristics in the form of a Nyquist diagram. It is proved that such a system will be stable when the chart of its Nyquist diagram does not cover a point with coordinates [+1, 0] on the complex plane. The validity of the new criterion has been confirmed by comparing the simulation results in the time range with the location of the Nyquist diagram on the complex plane. Based on the new criterion of stability, an algorithm for automatic construction of a Stability Lobes Diagram (SLD) has been developed. The necessary a priori parameters of TMS, the ranges of frequency change, and the calculation step for constructing such a characteristic in the coordinates "cutting depth – spindle rotational speed" have been determined. The adequacy of the obtained results is confirmed by a full-scale experiment to assess the roughness of machined parts under cutting modes that fall into the area of stability and instability on the SLD chart. The full-scale experiment proved the possibility of a significant reduction in roughness according to the Rz parameter, from 43 µm to 18 µm, while increasing productivity by 1.28 times. The use of a stability lobes diagram is especially effective when programming CNC lathes where it is possible to select the spindle speed in a wide range.
Robust output feedback learning control for induction motor servo drives

This paper addresses the output feedback tracking control problem for induction motor servo drives with mechanical uncertainties: rotor angle, rotor speed and stator currents are assumed to be available for feedback. A robust adaptive learning control is designed under the assumption that the reference profile for the rotor angle is periodic with known period: it ‘learns’ the periodic disturbance signal by identifying the Fourier coefficients of any truncated approximation; ℒ︁2 and ℒ︁∞ transient performances are guaranteed in the ‘learning phase’. It is shown that, for any motor initial condition belonging to an arbitrary given compact set, by properly setting the control parameters: (i) the rotor position and flux modulus tracking errors exponentially converge to residual sets, which may be arbitrarily reduced by increasing the number of terms in the truncated Fourier series; (ii) when the unknown periodic disturbance can be represented by a finite Fourier series, the rotor position and flux modulus tracking errors exponentially converge to zero. As in field oriented‐control, the control algorithm generates references for the magnetizing flux component and for the torque component of the stator current leading to significant simplifications for current‐fed motors. Copyright © 2008 John Wiley & Sons, Ltd.
The Autonomous Lagrangian Circulation Explorer (ALACE)

Abstract The autonomous Lagrangian circulation explorer (ALACE) is a subsurface float that cycles vertically from a depth where it is neutrally buoyant to the surface where it is located by, and relays data to, System Argos satellites. ALACEs are intended to permit exploration of large-scale low-frequency currents and to provide repeated vertical profiles of mean variables. ALACEs periodically change their buoyancy by pumping hydraulic fluid from an internal reservoir to an external bladder, thereby increasing float volume and buoyancy. Because positioning and data relay are accomplished by satellite, ALACEs are autonomous of acoustic tracking networks and are suitable for global deployment in arrays of any size. While providing only a sequence of displacements between surfacing intervals, ALACEs are efficient in gathering the widely spaced long-term observations needed to map large-scale average flow. The primary technical challenges met in the ALACE design are maximizing energy efficiency to achieve a l.
Development of Electromagnetic-Wave-Shielding Polyvinylidene Fluoride–Ti3C2Tx MXene–Carbon Nanotube Composites by Improving Impedance Matching and Conductivity

Absorption-dominated electromagnetic interference (EMI) shielding is attained by improving impedance matching and conductivity through structural design. Polyvinylidene fluoride (PVDF)–Ti3C2Tx MXene–single-walled carbon nanotubes (SWCNTs) composites with layered heterogeneous conductive fillers and segregated structures were prepared through electrostatic flocculation and hot pressing of the PVDF composite microsphere-coated MXene and SWCNTs in a layer-by-layer fashion. Results suggest that the heterogeneous fillers improve impedance matching and layered coating, and hot compression allows the MXene and SWCNTs to form a continuous conducting network at the PVDF interface, thereby conferring excellent conductivity to the composite. The PVDF-MXene-SWCNTs composite showed a conductivity of 2.75 S cm−1 at 2.5% MXene and 1% SWCNTs. The EMI shielding efficiency (SE) and contribution from absorption loss to the total EMI SE of PVDF-MXene-SWCNTs were 46.1 dB and 85.7%, respectively. Furthermore, the PVDF-MXene-SWCNTs composite exhibited excellent dielectric losses and impedance matching. Therefore, the layered heteroconductive fillers in a segregated structure optimize impedance matching, provide excellent conductivity, and improve absorption-dominated electromagnetic shielding.
Correlations between Maternal and Fetal Outcomes in Pregnant Women with Kidney Failure

Background: Kidney function impairment in pregnancy is challenging, with incidence and prognosis only partially known. Studies concerning maternal and fetal outcomes in pregnancies occurring in patients with renal injury and the therapeutic strategies for improving the prognosis of these patients are scarce due to the limited number of cases reported. Objectives: We aimed to establish correlations between the main maternal and fetal outcomes in patients with severe CKD or AKI in pregnancy to improve the prognosis, referring to a control group of patients with mild kidney impairment. Methods: For this purpose, we conducted a retrospective study, at University Emergency Hospital in Bucharest, Romania, from January 2019 until December 2021, selecting 38 patients with AKI and 12 patients diagnosed with advanced CKD, compared to 42 patients displaying borderline values of serum creatinine (0.8–1 mg/dL), reflecting the presence of milder kidney impairment. Results: The probability of having a child that is premature and small for gestational age, with a lower Apgar score and more frequent neonatal intensive care unit admissions, delivered by cesarean section, is higher in patients with highly reduced kidney function. Conclusion: Severe kidney function impairment is associated with a grim fetal prognosis and obstetrical complications.
On Saturnian cosmic ray cutoff rigidities

The theory of charged particle motion in a dipole field has been well developed, however because of the importance to the geomagnetic field of contributions other than dipolar, interest in the subject has remained primarily pedagogical over the past decade. Recent measurements by Ness et al. and Smith et al. have shown that the magnetic field of Saturn is essentially dipolar, with the axis of the dipole approximately aligned with the planetary rotation axis. This note briefly sketches the dipole geomagnetic cutoff theory and demonstrates the scaling required for its applicability to energetic particle measurements in the vicinity of Saturn.
Magnetic interactions in dot arrays with perpendicular anisotropy

The ΔM method is based on the difference of field-induced magnetization M(H) curves starting from different initial states. It is widely used to determine the magnetic interactions in recording media made of granular or self-organized nanoparticles. It is applied here to a two-dimensional Ising model system of interacting magnetic dots fabricated by focused ion-beam patterning. This allowed us to vary the sign and the strength of the interparticle coupling in a controlled way. By high-resolution magneto-optical microscopy, the local switching processes have been investigated for these dot arrays, giving insight into the understanding of the ΔM method. Numerical simulations, using realistic values of the interactions, allowed us to reproduce well the observed field-induced magnetic domain patterns and to fit the M(H) and ΔM(H) curves.
Bjerknes forces between two bubbles in a viscous fluid

A refined expression for the secondary Bjerknes force between two spherical gas bubbles in a viscous incompressible fluid is derived, allowing for the dipole oscillations of the bubbles and acoustic streaming around them. The investigation is motivated by the fact that the existing theory [see, for example, E. A. Zabolotskaya, Sov. Phys. Acoust. 30, 365–368 (1984)] neglects both of these processes, taking into account only linear viscous effects due to the radial oscillations of the bubbles. More correct calculations reveal that, provided the viscous penetration depth in the surrounding fluid is comparable to the bubble size, the forces on the bubbles differ noticeably from values given by the former theory, and, in addition, are no longer equal and opposite to each other. Such conditions are shown by numerical examples to be quite realistic ones, even for low-viscosity fluids like water.
How and When Does Mandatory CSR Disclosure Affects Firms’ CSR Disclosure Strategy?

ABSTRACT Research on corporate social responsibility (CSR) disclosure recognizes the importance of the government and examines how firms respond to government CSR regulations. However, little attention is given to how government regulations affect firms’ disclosure strategy in multiple fields of CSR. Based on institutional theory, this study proposes that mandatory CSR disclosure increases the legitimacy management cost for firms, and thus firms disclose more CSR scope to gain legitimacy and less CSR emphasis to reduce costs. Using data from Chinese A-share listed firms in 2008–2018, this study finds that mandatory CSR disclosure is positively related to CSR scope but negatively related to CSR emphasis. In addition, firm visibility strengthens the aforementioned positive and negative relations, whereas market competition weakens the relation between mandatory CSR disclosure and CSR emphasis. This study contributes to the literature on CSR disclosure and studies on organizational responses to the government mandate. 虽然关于企业社会责任信息披露的研究认识到政府的重要性，并考察了企业如何响应政府的社会责任规定，但是，鲜有研究考察政府的规定如何影响企业在多个社会责任领域的披露策略。 本文作者基于制度理论，提出强制性企业社会责任披露增加了企业的合法性管理成本，因而企业会披露较多的社会责任范围来获得合法性，而披露较少的企业社会责任的着重点以降低成本。 本研究利用2008-2018年中国A股上市公司的数据进行分析，发现强制性企业社会责任披露确实与企业社会责任披露的范围呈正相关，而与企业社会责任披露的着重点呈负相关。 此外，企业知名度加强了上述的正、负关系；而市场竞争削弱了强制性企业社会责任披露与企业社会责任披露着重点之间的负关系。 本研究对企业社会责任披露文献和组织响应政府规定的文献做出了贡献。
Causes of Immediate and Early IOP Spikes After Circumferential Gonioscopy-Assisted Transluminal Trabeculotomy Using ASOCT

Purpose To report the early postoperative causes of intraocular pressure (IOP) spikes after complete circumferential gonioscopy-assisted transluminal trabeculotomy (GATT) using anterior segment optical coherence tomography (ASOCT). Methods This was retrospective interventional case series of patients who underwent circumferential GATT by a single surgeon (APR) from 2021 to 2022 at a tertiary eye care in East India and who developed IOP spikes at 1 day-2 weeks (immediate) or early (>2 weeks–2 months) after GATT. The intraocular pressure (IOP), glaucoma medications, and angle evaluation by ASOCT at 1 week, and 1 month were compared between the two groups. Results Thirty-two eyes of 32 consecutive patients, aged 40±20.1 years (20 exfoliation glaucoma, 9 juvenile open-angle, and 3 developmental glaucoma), that developed IOP spikes between immediate (n=20) or early (n=12) IOP spikes after GATT, were included. Immediate postoperative spikes were seen in 20 eyes due to retained viscoelastic (n=8), hyphema (n=8) in uncontrolled hypertension, and peripheral anterior synechiae (PAS) (n=6) of which only one eye required medication at 2 months. Causes of immediate IOP spikes on ASOCT included an inverted/reattached trabecular shelf, iris strands in eyes with abnormal iris in developmental glaucoma, and PAS in 1–2 quadrants. Causes of early IOP spikes included PAS >3 quadrants (n=8), and hyperreflective fibrotic tissue over TM (n=4) with 50% requiring medications at 2 months. The ASOCT features predicting the need for medications were PAS >3 quadrants (OR=8.4[2.2–14.3], p=0.03) and fibrotic TM closure (OR=5.4, [3.6–10.2], p=0.003). One eye with macrohyphema 3 days after surgery owing to uncontrolled hypertension (owing to the stoppage of medicines), required additional incisional trabeculectomy within 1 month of surgery. Conclusion Immediate IOP spikes are mostly self-resolving as opposed to early IOP spikes >2 weeks that require medications after GATT. Gonioscopic PAS >3 quadrants, and fibrotic TM closure were the main identifiable ASOCT causes predicting the need for medications after GATT.
Enhanced Color Conversion of Quantum Dots Located in the Hot Spot of Surface Plasmon Coupling

For improving the performance of the photon color conversion from the energy of an InGaN/GaN quantum-well (QW) structure into the longer-wavelength emission of a colloidal quantum dot (QD), we insert the photoresist solution of the QD into a surface nano-hole, whose bottom face is about 10 nm higher than the top QW. The sample top surface is then cleaned for depositing Ag nanoparticles (NPs) to induce the surface plasmon (SP) coupling with the QW structure such that the QDs inside the nano-holes are located in the region of strong field distribution (hot spot). In this situation, the SP coupling can enhance the Förster resonance energy transfer (FRET) from QW into QD and the QD emission efficiency for producing a stronger color conversion process. The nanoscale-cavity effect of the nano-hole structure can further strengthen the SP-coupling enhanced FRET and QD emission.
Design of a Fuel Explosion-Based Chameleon-Like Soft Robot Aided by the Comprehensive Dynamic Model

Soft robotics have advantages over the traditional rigid ones to achieve the bending motion but face with challenges to realize the rapid and long-distance linear motion due to the lack of a suitable actuation system. In this paper, a new explosion-based soft robot is proposed to generate the axial fast extension by the explosion pressure. To support and predict the performance of this explosion-based soft robot, a novel dynamic model is developed by considering the change of working fluid (molecular numbers) and some unavoidable and influential factors in the combustion process. Then, based on the physical prototype, a set of experiments is conducted to test the performance of the explosion-based soft robot in performing the axial extensions, as well as to validate the model proposed in this article. It is found that the novel explosion-based soft robot can achieve rapid axial extension by the developed explosion-based actuation system. The explosion-based soft robot can achieve 41-mm displacement at a fuel mass of 180 mg. In addition, the proposed dynamic model can be validated with an average error of 1.5%. The proposed approach in this study provides a promising solution for future high-power density explosion-based soft robots.
First-principles relativistic theory of the magnetic response of paramagnetic metals: Application to yttrium and scandium

We describe a first-principles theoretical formalism for the magnetic response of paramagnetic metals in which all relativistic effects such as spin-orbit coupling are included. In particular, the easy axis and dependence upon wave vector q of the paramagnetic spin susceptibility x(q) can be calculated. To illustrate we apply the method to two transition metals, yttrium and scandium. In each case we findx(q) to peak at a wave vector q5(0,0,0.57) p/c, coincident with a Fermi surface nesting vector, and to have an easy axis perpendicular to q. Since x(q) plays a key role in determining the interaction between magnetic impurities in these metals, these results are consistent with the helical antiferromagnetic order found in many dilute rare-earth Y alloys. Conversely, the easy axis for the response to a uniform magnetic field, q50, lies along the c axis.
Agnostic CH-DT Technique for SCADA Network High-Dimensional Data-Aware Intrusion Detection System

The pervasiveness in the Industrial Internet of Things (IIoT) due to the application of supervisory control and data acquisition (SCADA) has led to the growth of heterogeneous sensor data, thereby increasing the risk of intrusions and attacks. The existence and effect of intruders and their innovative attack techniques are on the rise. Existing intrusion detection systems (IDSs) tend to be computationally expensive with this form of data due to the presence of noise. In real-time domains, available methods lag, necessitating additional research into effective feature extraction schemes, which is fundamental in machine learning (ML) for time exigency. This study, in a comparative analysis of some feature selection techniques (FS), proposes a combination of an efficient ML classifier and an agnostic FS scheme for attack detection and classification in a real-time SCADA network. The flexibility and interoperability of the proposed approach resolve the computational complexity of vulnerability detection schemes while reducing false alarm rates (FARs) and overall model execution time. With the view of an online preprocessing, the proposed technique is phased, thus: 1) data preparatory consisting of data cleansing and normalization followed by 2) the combination of a prepruned decision tree (DT) algorithm and an agnostic chi-square FS approach built to obtain an optimal subset of data features for efficient IDS; and 3) evaluation of proposed agnostic DT-CH and other FS candidates for anomaly detection.