The relationship between pangolin-CoV and SARS-CoV-2 has been a subject of debate. Further evidence of a special relationship between the two viruses can be found by the fact that all known COVID-19 viruses have abnormally hard outer shell (low M disorder; i.e., low content of intrinsically disordered residues in the membrane (M) protein) that so far was found in CoVs associated with burrowing animals, such as rabbits and pangolins, in which transmission involves virus remaining in buried feces for a long time. While a hard outer shell is necessary for viral survival, a harder inner shell could also help. For this reason, the N disorder range of pangolin-CoVs, not bat-CoVs, more closely matches that of SARS-CoV-2 especially when Omicron is included. The low N disorder (i.e., low content of intrinsically disordered residues in the nucleocapsid (N) protein), first observed in pangolin-CoV-2017 amd later in Omicron, is associated with attenuation according to the Shell-Disorder-Model. Our experimental study revealed that pangolin-CoV-2017 and SARS-CoV-2 Omicron (XBB.1.16 subvariant) show similar attenuations with respect to viral growth and plaque formation. Subtle differences have been observed that are consistent with disorder-centric computational analysis.

User-generated passwords often pose a security risk in authentication systems. However, providing a comparative substitute poses a challenge, given the common tradeoff between security and user experience. This paper integrates cryptographic methods (both asymmetric and symmetric), steganography, and a combination of physiological and behavioral biometrics to construct a prototype for a passwordless authentication system. We demonstrate the feasibility of scalable passwordless authentication while maintaining a balance between usability and security. We employed threat modeling techniques to pinpoint the security prerequisites for the system, along with choosing appropriate cryptographic protocols. In addition, a comparative analysis is conducted, examining the security impacts of the proposed system in contrast to that of traditional password-based systems. Results from the prototype indicate that authentication is possible within a timeframe similar to passwords (within 2 seconds), without imposing additional hardware costs on users to enhance security or compromising usability. Given the scalable nature of the system design and the elimination of shared secrets, the financial and efficiency burdens associated with password resets are alleviated. Furthermore, the risk of breaches is mitigated, as there is no longer a need to store passwords and/or their hashes. Differing from prior research, our study presents a pragmatic design and prototype that deserves consideration as a viable alternative for both password-based and passwordless authentication systems.

Authentication systems based on biometrics characteristics and data represents one of the most important trend in the evolution of our world. In the near future, biometrics systems will be everywhere in the society, such as government, education, smart cities, banks etc. Due to its uniqueness characteristic, biometrics systems will become also vulnerable, privacy being one of the most important challenge. The classic cryptographic primitives are not sufficient to assure a strong level of secureness for privacy. The following work paper represents an effort to present the main cryptographic techniques and algorithms that can give us the possibility to raise a certain level of secureness for privacy. We will show their own challenges (strengths and weaknesses). We will demonstrate how we can use the most common and well-known techniques and algorithms in order to get a maximum efficiency and a high level in assuring the integrity of the biometrics data.

The rapid growth of smartphone financial services raises the need for secure mobile authentication. Continuous authentication is a user-friendly way to strengthen the security of smartphones by implicitly monitoring a user’s identity through sessions. Mobile continuous authentication can be viewed as an anomaly detection problem in which models discriminate between one genuine user and the rest of the imposters (anomalies). In practice, complete imposter profiles are hardly available due to the time and monetary cost, while leveraging genuine data alone yields poor generalized models due to the lack of knowledge about imposters. To address this challenge, we recast continuous mobile authentication as a few-shot anomaly detection problem, aiming to enhance the inference robustness of unseen imposters by using partial knowledge of available imposter profiles. Specifically, we propose a novel deep learning-based model, namely Local Feature Pooling based Temporal Convolution Network (LFP-TCN), which directly models raw sequential mobile data, aggregating global and local feature information. In addition, we introduce a random pattern mixing augmentation to generate class-unconstrained imposter data for the training. The augmented pool enables characterizing various imposter patterns from limited imposter data. Finally, we demonstrate practical continuous authentication using score-level fusion, which prevents long-term dependency or increased model complexity due to extended re-authentication time. Experiments on two public benchmark datasets show the effectiveness of our method and its state-of-the-art performance.

Tellurium exhibits exceptional intrinsic electronic properties. However, investigations into the modulation of tellurium's electronic properties through physical modification are notably scarce. Here, we present a comprehensive study focused on the evolution of the electronic properties of tellurium crystal flakes under plasma irradiation treatment by employing conductive atomic force microscopy and Raman spectroscopy. The plasma-treated tellurium experienced a process of defect generation through lattice broken. Prior to the degradation of electronic transport performance due to plasma irradiation treatment, a remarkable observation emerged: in the low-energy region of hydrogen plasma-treated tellurium, a notable enhancement in conductivity was unexpectedly detected. The mechanism underlying this enhancement in electronic transport performance was thoroughly elucidated by comparing it with the electronic structure induced by argon plasma irradiation. This study not only fundamentally uncovers the effects of plasma irradiation on tellurium crystal flakes, but also unearths an unprecedented trend of enhanced electronic transport performance at low irradiation energies when utilizing hydrogen plasma. This abnormal trend bears significant implications for guiding the prospective application of tellurium-based 2D materials in the realm of electronic devices.

Fighting against the COVID-19 pandemic caused by the SARS-CoV-2 virus is one of the most critical challenges facing the global health system today. The possibility to identify the group of persons in the cohort of people under 50 years old, who are sensitive to the COVID-disease by non-invasive methods, is a very perspective approach for estimating the epidemiological state of the human population. The study aimed to identify the features of people's faces with COVID-19 that the most correlate with disease severity could serve as one of these approaches. For this aim, 525 photos of patients' faces with different outcomes of COVID-19 disease were analyzed using the Dlib face recognition convolutional neural network pre-trained for face recognition. Face descriptor vectors were obtained using the convolutional neural network. Facial features were found that predict a person's sensitivity to the SARS-CoV-2 virus (disease severity), and the contribution of each of the features to the risk of developing a severe form of COVID in a person was found. The accuracy of the binary classification of the individual severity of the COVID-19 course using the k-nearest neighbors algorithm on the test dataset was accuracy - 84%, AUC - 0.90.

In addressing the challenges of data scarcity in biometrics, this study explores the generation of synthetic palmprint images as an efficient, cost effective, and privacy preserving alternative to real-world data reliance. Traditional methods for synthetic biometric image creation primarily involve orientation modifications and filter applications, with no established method specific to palmprints. We introduced the utilization of the “Style-based generator”, StyleGAN2-ADA, from the StyleGAN series, renowned for generating high-quality images. Furthermore, we explore the capabilities of its successor, StyleGAN3, which boasts enhanced image generation, facilitating smooth and realistic transitions. By comparing the performance of StyleGAN3 on public dataset, we aim to establish the most efficient generative model for this purpose. Evaluations were conducted using the SIFT (Scale-Invariant Feature Transform) algorithm into our evaluation framework. Preliminary findings suggest that StyleGAN3 offers superior generative capabilities, enhancing equivariance in synthetic palmprint generation.

In 1999, Molodtsov initiated the theory of soft sets as a new mathematical tool for dealing with uncertainties in many fields of applied sciences. In 2011, Shabir and Naz introduced and studied the notion of soft topological spaces, also defining and investigating many new soft properties as generalization of the classical ones. In this paper, we introduce the notions of soft separation between soft points and soft closed sets in order to obtain a generalization of the well-known Embedding Lemma to the class of soft topological spaces.

This article focuses on developing a continuous authentication system using behavioral biometrics to recognize users accessing computing devices. The user’s distinct behavioral biometric is captured through keystroke dynamics, and reward-based reinforcement learning (RL) ideas are applied to recognize them throughout the session. The suggested system adds an extra layer of security to traditional authentication methods, forming a robust continuous authentication system that can be added to static authentication systems. The methodology involves training a RL model to detect unusual user typing patterns and flag suspicious activity. Each user has an agent trained on their historical data, which is preprocessed and used to create episodes for the agent to learn from. The environment involves fetching observations and randomly corrupting them to learn out-of-order behavior. The observation vector includes both running features and summary features. The re-ward function is binary and minimalistic. The Principal Component Analysis (PCA) model is used to encode the running features, and the Double Deep Q-Network (DDQN) algorithm with a fully connected neural network is used as the policy net. The evaluation achieved an average training accuracy and EER (equal error rate) of 94.7% and 0.0126 and test accuracy and ERR of 81.06% and 0.0323 for all users when the number of encoder features was increased. Therefore, it is concluded that by continuously learning and adapting to changing behavior patterns, this approach can provide more secure and personalized authentication, lowering the possibility of unauthorized access and cyberattacks. Overall, the use of reinforcement learning and behavioral biometrics for continuous authentication has the potential to significantly enhance security in the digital age and are effective in identifying each user.

In this paper, we first define the concepts of r-fuzzy soft α-open (semi-open and δ-open) sets on fuzzy soft topological spaces based on the article Aygunoglu et al. (Hacet. J. Math. Stat., 43 (2014), 193-208), and the relations of these sets with each other are established. In addition, we introduce the concepts of fuzzy soft δ-closure (δ-interior) operators, and study some properties of them. Also, the concept of r-fuzzy soft δ-connected sets is introduced and studied with help of fuzzy soft δ-closure operators. Thereafter, we define the concepts of fuzzy soft α-continuous (β-continuous, semi-continuous, pre-continuous and δ-continuous) functions, which are weaker forms of fuzzy soft continuity, and some properties of these functions along with their mutual relationships are discussed. Moreover, a decomposition of fuzzy soft α-continuity and a decomposition of fuzzy soft semi-continuity is obtained. Finally, as a weaker form of a fuzzy soft continuity, the concepts of fuzzy soft almost (weakly) continuous functions are defined, and some properties are specified. Additionally, we explore the notion of continuity in a very general setting called, fuzzy soft (L, M, N, O)-continuous functions and a historical justification is introduced.

Proteins have the ability to adsorb on the surface of materials, such as soft contact lenses (SCLs), and can affect the hydrophobicity, roughness and surface properties of the contact lenses (CLs), which, in turn, can influence the friction between the lenses and the ocular surface. Excessive friction between contact lenses and the ocular surface can lead to discomfort for the wearer and may cause irritation or inflammation of the cornea, better known as corneal ulcers (keratitis). Bovine serum albumin (BSA) is often used as a standard protein in biocompatibility testing of materials, including contact lenses. One standard commercial contact lenses was tested under lubricated conditions to access the coefficient of friction (CoF), being the contact lubricated with a tear like fluid (TLF) solution containing six different concentrations of BSA. In all cases, a good linearity of the results of the friction force was verified, so the first friction law can be applied to determine the value of the coefficient of friction. It was found that friction increases with increasing protein concentration.

Background: One challenge in implant dentistry is to reduce marginal bone resorption to avoid long-term esthetic and biological complications. Sub-gingival implant placement has been suggested as a suitable strategy. Methods: 38 healthy patients were enrolled to receive bone level (BL – Control group) or 2 mm sub-crestal (SC - Test group) conical connection, platform-switched implants. An immediate tissue level abutment was used in the Test group by following a One Time Abutment (OTA) restorative procedure. Marginal Bone Modification (MBM) was calcu-latied on standardized radiographs at surgery (T0), loading (T1), and 6 months (T2) and 12 months after loading (T3), and cathegorised in Bone Loss (BL) if the resorption occurred below the implant neck and Bone Remodeling (BR) if above. Pocket probing depth (PPD), Bleeding on probing (BoP) and Plaque Index (PI) were also collected. Results: The mean MBM in the test group after 12 months was 0.61mm, compared to 0.52mm in the control group. However, no BL was observed in the test group, as the MBM completely occurred above the implant neck as BR, whilst in the control group MBM corresponded in total to BL. The average PPD was 2.38mm in the test group and 3.04mm in the control group after 12 months, BoP 50% and 43%, PI 33% and 19.44% respectively. Conclusions: Sub-crestal conical connection, platform-switched implants could be a suitable clinical choice to avoid BL with exposure of the treated implants surfaces.

The present review compared the efficacy of soft tissue substitutes (STS) and autogenous free gingival graft (FGG) or connective tissue graft (CTG) in mucogingival procedures to increase keratinized tissue (KT) width around teeth and implants. Two independent examiners performed the electronic search on Medline and Cochrane Library based on the following PICO’s format: (P) adult patients; (I) soft tissue substitutes and FGG/CTG; (C) STS vs CTG; STS vs FGG; STS vs CTR; (O) KT width gain; (S) Systematic Reviews, Randomized Controlled Trials. Results showed that around teeth, all biomaterials showed superior performance compared to CAF alone for treating gingival recessions. However, when compared to CTG, ADM yields the most similar outcomes to the gold standard (CTG), even though in multiple recessions CTG still continue to be considered the most favorable approach. Use of STSs (acellular matrix or tissue engineered) in combination with an apically positioned flap resulted in a significantly less gain of KTW compared to what achieved with FGG and APF. Around dental implants, free gingival grafts were deemed more effective than soft tissue substitutes in enhancing keratinized mucosa width.

In this manuscript, we first introduce some properties of r-fuzzy soft α-open sets in fuzzy soft topological spaces based on the manuscript Aygunoglu et al. (Hacet. J. Math. Stat. 2014, 43, 193-208). In addition, we define the concepts of fuzzy soft α-closure (α-interior) operators, and investigate some properties of them. Furthermore, the concept of r-fuzzy soft α-connected sets is defined and characterized with help of fuzzy soft α-closure operators. Thereafter, we introduce and study the concepts of fuzzy soft almost (weakly) α-continuous mappings, which are weaker forms of fuzzy soft α-continuous mappings, and we discuss some properties of fuzzy soft α-continuity. Moreover, we establish that fuzzy soft α-continuity → fuzzy soft almost α-continuity → fuzzy soft weakly α-continuity, but the converse may not be true. It is also we show that the composition is fuzzy soft almost α-continuous mapping if, is fuzzy soft α-continuous mapping and is fuzzy soft almost continuous mapping. Finally, some new types of compactness via r-fuzzy soft α-open sets are defined, and the relationships between them are examined.

Two polyurethanes (PUs) were similarly synthesized by reacting a cycloaliphatic isocyanate with 1,4 butanediol and two polyols of different nature (polyester, polycarbonate diol) with molecular weights of 1000 Da. The PU made with polycarbonate diol polyol (YCD) was the only showing intrinsic self-healing at 20 °C. For assessing the mechanism of intrinsic self-healing of YCD, a structural characterization by molecular weights determination, infrared and X-ray photoelectronic spectroscopies, differential scanning calorimetry, X-ray diffraction, thermal gravimetric analysis and dynamic mechanical thermal analysis was carried out. It was concluded that the self-healing at 20 °C of YCD was due to non-covalent dynamic exchange interactions among the carbonate groups of the soft segments. Therefore, the chemical nature of the polyol played a key role in developing PUs with intrinsic self-healing at 20 °C.

The paper explores the Kullback-Leibler divergence formalism (KLDF) applied to the stable MG1 queue manifold. More potentially, both service time probability and cumulative functions which make KLDF exact are obtained. The credibility of KLDF is justified through consistency axioms. Some potential applications of Kullback-Leibler divergence to Biometry are presented. The paper concludes with closing remarks combined with some challenging open problems and the next phase of research.

In this article, we introduce the concept of soft intervals, soft ordering and sequences of soft real numbers, and some of their structural properties are studied. The notion of soft Lebesgue measure on the soft real numbers has been introduced. Also, a correspondence relationship has been established between the soft Lebesgue measure and the classical Lebesgue measure. Furthermore, we have studied some exciting results and relations between the soft Lebesgue measure and the Lebesgue measure of soft real sets.

The study of pain requires a balance between subjective methods that rely on self-reports and complementary objective biometrics that ascertain physical signals associated with subjective accounts. There are at present no objective scales that enable the personalized assessment of pain, as most work involving electrophysiology rely on summary statistics from a priori theoretical population assumptions. Along these lines, recent work has provided evidence of differences in pain sensations between participants with Sensory Over Responsivity (SOR) and controls. While these analyses are useful to understand pain across groups, there remains a need to quantify individual differences more precisely in a personalized manner. Here we offer new methods to characterize pain using the moment-by-moment standardized fluctuations in EEG brain activity centrally reflecting the person’s experiencing temperature-based stimulation at the periphery. This type of gross data is often disregarded as noise, yet here we show its utility to characterize the lingering sensation of discomfort raising to the level of pain, individually, for each participant. We show fundamental differences between the SOR group in relation to controls and provide an objective account of pain congruent with the subjective self-reported data. This offers the potential to build a standardized scale useful to profile pain levels in a personalized manner across the general population.

Amylose content (AC) stands as a pivotal determinant of rice grain quality, primarily governed by the Waxy gene (Wx), with its allelic diversity significantly influencing AC variation. In the current culinary landscape, soft rice varieties, known for their low AC and superior palatability, are particularly sought after by consumers. Notably, many soft japonica rice varieties cultivated in southern China, including the Nangeng series, are characterized by the presence of the Wxmp allele, derived from the ancestral Wxmq allele. While both alleles are associated with reduced AC, there remains a paucity of detailed understanding regarding the interplay between specific functional single nucleotide polymorphisms (SNPs) within these alleles and the overarching rice grain quality. Employing site-directed mutagenesis, we engineered three distinct transgenic rice lines, each harboring either the Wxmp, Wxmq, or Wxb-5c alleles, against the background of the glutinous rice cultivar Nip(wx). This suite of transgenic rice showcased a gradation ingrain transparency inversely correlated to AC, delineating a sequence from Wxmq, signifying the lowest, through Wxmp, to Wxb-5c, indicating the highest. Consequently, this gradation in AC precipitated variations in other rice grain physicochemical attributes, such as the taste value of cooked rice, gel consistency (GC), and starch pasting properties. Furthermore, analyses of gene expression and enzyme activity revealed that the functional SNPs, Ex4-53G/A and Ex5-53T/C, lead to a decline in the GBSSI enzyme activity without affecting expression levels. These findings underscore the potential of harnessing these SNPs in breeding programs aimed at developing soft rice varieties endowed with enhanced culinary qualities.

The advantage of FPGAs lies in the ability to implement a fully hardware solution for interfacing with various input/output (I/O) devices. Each block can work in parallel with all the others, simplifying the satisfaction of timing constraints. However, this hardware utilization consumes FPGA resources that could otherwise be allocated to the primary project. An alternative involves employing a small "soft-core" processor implementing I/O in software. With the goal to design and evaluate a new tiny soft-core processor optimized for FPGA resources in I/O , a novel processor named Baby8 is developed. It is an 8-bit CISC soft-core processor optimized for reduced FPGA resources including program size for 8-bit applications. The number of instructions is not large but any instruction can access arbitrary memory locations. The performance and resource utilization of the newly designed processor are evaluated and compared with a variety of other soft-core processors. The results demonstrate its competitive performance, achieving an average maximum clock frequency of approximately 57 MHz and a power consumption of around 2mW. Furthermore, it conserves nearly half of the FPGA resources in implementation.

The soft robot has many degrees of freedom, strong environmental adaptability and good human-computer interaction ability. As the end-effector of the soft robot, the soft gripper can grasp objects of different shapes without destructivity. Based on the theoretical analysis of the soft robot, the kinematics model of the flexible gripper and the theoretical model of the bending deformation of the air cavity were established. Accordingly, the relationship between the bending angle of the soft gripper and the air pressure was determined. Through the application of finite element software, the bending degree of pneumatic network multi-cavity soft gripper was simulated by finite element software, and the influence of structural parameters of soft actuator on bending deformation was determined. In addition, with the 3D technology conducting the printing of soft gripper fixtures and molds, the injection molding the actuator and the human-computer interaction interface controlling the movement of the gripper, the adaptability of the soft gripper in grasping object was verified. The result shows that the software gripper possesses good flexibility and can better grasp objects of different shapes.

Soft robotic manipulators consisting of serially-stacked segments combine actuation and structure in an integrated design. This design can be miniaturised while providing suitable actuation for applications such as minimally invasive surgery and for inspections in confined environments. The control of these robots, however, remains challenging, due to the difficulty in accurately modelling the robots, in coping with their redundancies, and in solving their full inverse kinematics. In this work, we explore a hybrid approach to control serial soft robotic manipulators that combines machine learning (ML) to estimate the inverse kinematics with a closed-loop control to compensate the remaining errors. For the ML part, we compare various approaches, including both kernel-based learning and more general neural networks. We validate the selected ML model experimentally. For the closed-loop control part, we first explore Jacobian formulations using both synthetic models and numerical approximations from experimental data. We then implement integral control actions using both these Jacobians, and evaluate them experimentally. In an experimental validation, we demonstrate that the hybrid control approach achieves setpoint regulation in a robot with 6 inputs and 4 outputs.

In the present study. At first, some properties of r-fuzzy soft β-closed sets are introduced on fuzzy soft topological spaces based on the paper Aygunoglu et al. (Hacet. J. Math. Stat. 2014, 43, 193-208). Also, we define the closure and interior operators with respect to the classes of r-fuzzy soft β-closed and r-fuzzy soft β-open sets, and investigate some of their properties. In addition, the concept of r-fuzzy soft β-connected sets is introduced and characterized with help of fuzzy soft β-closure operators. Thereafter, some properties of a fuzzy soft β-continuity are studied. Furthermore, we introduce and study the concepts of fuzzy soft almost (weakly) β-continuous functions, which are weaker forms of a fuzzy soft β-continuity. Also, the relationships between these classes of functions are specified with the help of some illustrative examples. Finally, we explore new types of fuzzy soft functions called, fuzzy soft β-irresolute (strongly β-irresolute, β-irresolute open, β-irresolute closed and β-irresolute homeomorphism) functions, and discuss some properties of them. Also, we show that fuzzy soft strongly β-irresolute → fuzzy soft β-irresolute → fuzzy soft β-continuity, but the converse may not be true.

Knowledge graphs (KGs) play a crucial role in many applications, such as question answering, but incompleteness is an urgent issue for their broad application. Much research in knowledge graph completion (KGC) has been performed to resolve this issue. The methods of KGC can be classified into two major categories: rule-based reasoning and embedding-based reasoning. The former has high accuracy and good interpretability, but a major challenge is to obtain effective rules on large-scale KGs. The latter has good efficiency and scalability, but it relies heavily on data richness and cannot fully use domain knowledge in the form of logical rules. We propose a novel method that injects rules and learns representations iteratively to take full advantage of rules and embeddings. Specifically, we model the conclusions of rule groundings as 0-1 variables and use a rule confidence regularizer to remove the uncertainty of the conclusions. The proposed approach has the following advantages: 1) It combines the benefits of both rules and knowledge graph embeddings (KGEs) and achieves a good balance between efficiency and scalability. 2) It uses an iterative method to continuously improve KGEs and remove incorrect rule conclusions. Evaluations on two public datasets show that our method outperforms the current state-of-the-art methods, improving performance by 2.7% and 4.3% in mean reciprocal rank (MRR).

Confinement can induce substantial changes in the physical properties of macromolecules in suspension. Soft confinement is a particular class of restriction where the boundaries that constraint the particles in a region of the space are not well-defined. This scenario leads to a broader structural and dynamical behavior than the observed in systems enclosed between rigid walls. In this contribution, we study the ordering and diffusive properties of a two-dimensional colloidal model system subjected to a one-dimensional parabolic trap. Increasing the trap strength makes it possible to go through weak to strong confinement, allowing a dimensional transition from two- to one-dimension. The non-monotonic response of the static and dynamical properties to the gradual dimensionality change affects the system phase behavior. We find that the particle dynamics is connected with the structural transitions induced by the parabolic trap. In particular, at low and intermediate confinement regimes, complex structural and dynamical scenarios arise, where the softness of the external potential induces melting and freezing, resulting in faster and slower particle diffusion, respectively. Besides, at strong confinements, colloids move basically along one direction, and the whole system behaves structurally and dynamically similar to a one-dimensional colloidal system.

The reliability analysis allows to estimate the system's probability of detecting and identifying outlier. Failure to identify an outlier can jeopardise the reliability level of a system. Due to its importance, outliers must be appropriately treated to ensure the normal operation of a system. The system models are usually developed from certain constraints. Constraints play a central role in model precision and validity. In this work, we present a detailed optical investigation of the effects of the hard and soft constraints on the reliability of a measurement system model. Hard constraints represent a case in which there exist known functional relations between the unknown model parameters, whereas the soft constraints are employed for the case where such functional relations can slightly be violated depending on their uncertainty. The results highlighted that the success rate of identifying an outlier for the case of hard constraints is larger than soft constraints. This suggested that hard constraints should be used in the stage of pre-processing data for the purpose of identifying and removing possible outlying measurements. After identifying and removing possible outliers, one should set up the soft constraints to propagate the uncertainties of the constraints during the data processing. This recommendation is valid for outlier detection and identification purpose.

In this paper, we present the design, manufacturing and characterization of a soft textile-based clutch (TBC) that switches between locking and unlocking of its linear displacement by exploiting vacuum stimulation. The applied vacuum locks the relative sliding motion between two elaborated textile webbings covered by an elastic silicone rubber bag. Based on different fabrication techniques, such as silicone casting on textile, melt embossing for direct fabrication of miniature patterns on textile and sewing, we developed three groups of TBC samples based on friction and interlocking principles and we compared their performance in blocking configuration. The clutch with interlocking mechanism presented the highest withstanding force (150 N) respect to the one (54 N) recorded for the friction-based clutch. The simple and compact structure of the proposed clutch, together with the intrinsic adaptability of fabric with other clothing and soft materials, make it a proper solution for applications in soft wearable robotics and generally as locking and variable stiffness solution for soft robotic applications.

Biomimetic stimuli-responsive materials can respond to various external stimuli in the form of structural or morphological transformations by actively or passively converting input energy into mechanical energy. They are the core element of soft actuators for typical smart devices like soft robots, artificial muscles, intelligent sensors and nanogenerators. While significant progresses have been made in bioinspired stimuli-responsive materials, they have not yet achieved the remarkable properties in biological systems. In this review, we will discuss recent advances in biomimetic stimuli-responsive materials that are instrumental for soft actuators. Different stimuli-responsive principles for soft actuators are firstly discussed, including fluidic, electrical, thermal, magnetic, light and chemical stimuli. We further summarize the state-of-the-art stimuli-responsive materials for soft actuators and explore the advantages and disadvantages of using electroactive polymers, magnetic soft composites, hydrogels, liquid crystal elastomers, shape memory alloys and chemical-responsive materials. Finally, we provide a critical outlook on the field of stimuli-responsive soft actuators, and emphasize the challenges in the process of their implementation to various industries.

Plasmonics is the study of resonant oscillations of free electrons in metals caused by incident electromagnetic radiation. Surface plasmons can focus and steer light on the subwavelength scale. Apart from metals, plasmonic phenomena can be observed in soft matter systems such as electrolytes where resonant charge oscillations can be induced for ions in solution. Due to their larger mass, they are plasmon-active in a lower frequency regime and on a larger wavelength scale. Spatial confinement allows increasingly strong charge interactions and gives rise to nonlocality or spatial dispersion effects. These effects manifest as additional longitudinal propagation modes and are known to cause plasmonic broadening and resonance shifts in metal nanostructures. We derive and discuss the nonlocal optical response of ionic plasmons using a hydrodynamic, two-fluid model in a planar homogeneous three-layer system with electrolyte-dielectric interfaces. Studying such systems enables us to identify and understand plasmonic phenomena in biological and chemical systems.

Nowadays, the development or improvement of actuation mechanisms is a crucial topic for the achievement of dextrous manipulation using soft robots. Then, a primary target of research is the design of actuation and driving devices. Consequently, in this paper, we introduce a soft driving epicyclical mechanism that mimics human muscle behavior and fulfills motion requirements to achieve grasping gestures using a robotic finger. The prototype is experimentally assessed, and results show that our approach has enough performance for the implementation in grasping tasks. Furthermore, we introduce the basis for a new soft epicyclical mechanism merger with shape memory alloys to allow active stiffness control of the mechanism.

Soft set theory is a mathematical tool for dealing with uncertainty. This paper investigates limits of interval type of soft sets (for short, it-soft sets). The concept of it-soft sets is first introduced. Then, limits of it-soft sets are proposed and their properties are obtained. Next, point-wise continuity of it-soft sets and continuous it-soft sets are discussed. Finally, an application for rough sets is given.

In recent times, the soft robotics field is gaining numerous research focus owing to its high level of manipulation capabilities unlike traditional rigid robots, which gives room for an increasing use in other areas. However, compared to traditional rigid gripper robots, being capable of controlling/obtaining overall body stiffness when required is yet to be further explored since soft gripper robots have inherently less rigid properties. unlike previous designs with very complex variable stiffness systems, this paper demonstrates a soft gripper design with minimum system complexity while being capable of varying the stiffness of a continuum soft robotic actuator and proves to have potential applications in gripping objects of various shapes, weights & sizes. The soft gripper actuator comprises two separate mechanisms; the pneumatic mechanism for bending control and the mechanical structure for stiffness variation by pulling tendons using stepper motors which compresses the actuator, thereby changing the overall stiffness. The pneumatic mechanism was first fabricated and then embedded into another silicon layer during which it was as well merged with the mechanical structure for stiffness control. By first pneumatically actuating the actuator which causes bending and then pulling the tendons, we found out that the actuator stiffness value can be increased up to 145 % its initial value, and the gripper can grasp & lift a weight of up to 2.075 kg.

Background: Sarcoma may show similarities to malignant melanoma in terms of morphologic and immunohistochemical aspects, hence making it difficult to differentiate between these two neoplasms during the diagnostic process. This systematic review aims to summarize available evidence on cases of sarcoma that were initially diagnosed as melanoma. Methods: A comprehensive search was conducted including MEDLINE/Pubmed, EMBASE and SCOPUS through March 2023. We included case series and case reports of sarcoma patients that were initially diagnosed as malignant melanoma. PRISMA guidelines were followed. Results: Twenty-three case reports and four case series with a total of 34 patients were included. The clinical presentation was heterogeneous, and the most involved anatomical regions were lower limbs (24%), head/neck (24%) and upper limbs (21%). IHC positivity was reported for S100 (69%), HMB45 (63%), MelanA (31%) and MiTF (3%). The main reasons for second assessment were unusual presentation (48%) and uncertain diagnosis (28%). EWSR1 translocation was investigated in 17/34 patients (50%) and found positive in 16/17 (94%). The final diagnosis was clear cell sarcoma (50%) or other soft tissue sarcomas (50%). Conclusions: Melanoma and some histotypes of sarcoma share many similarities. In case of atypical lesions, a second diagnosis should be considered, and ESWR1 translocation should be investigated.

Palpation is a simple but effective method to differentiate tumors from healthy tissues. Development of miniaturized tactile sensors embedded on endoscopic or robotic devices are the key toward precise palpation diagnosis and the subsequent timely treatment. This paper reports on the fabrication and characterization of a novel tactile sensor with mechanical flexibility and optical transparency that can be easily mounted on soft surgical endoscopes and robotics. Utilizing the pneumatic sensing mechanism, the sensor offers a high sensitivity of 1.25 mbar and negligible hysteresis, enabling the detection of phantom tissues with different stiffnesses ranging from 0 to 2.5 MPa. Our configuration combining pneumatic sensing and hydraulic actuating also eliminates electrical wiring from the functional elements located at the robot end-effector, thereby enhancing the system safety. The optical transparency path in the sensors together with its mechanical sensing capability open interesting possibility in early detection of solid tumor as well as in the development of all in-one soft surgical robots that can perform visual/mechanical feedback and optical therapy.

Lignin has interesting functionalities to be exploited in adhesives for medicine, foods and textiles. Nanoparticles (NPs) <100 nm coated with poly(L-lysine), PL and poly(L-glutamic acid) PGA were prepared from the laccase treated lignin to coat nanocellulose fibrils (CNF) with heat. NPs ca. 300 nm were prepared, β-casein coated and cross-linked with transglutaminase (Tgase) to agglutinate chamois specimens. Size exclusion chromatography (SEC) and Fourier-transform infrared (FTIR) spectroscopy were used to characterize polymerized lignin, zetapotential and dynamic light scattering (DLS) to ensure coating of colloidal lignin particles (CLPs). Protein adsorption on lignin was studied by quartz crystal microbalance (QCM). Atomic force microscopy (AFM) was exploited to examine interactions between different polymers and to image NPs with transmission electron microscopy (TEM). Tensile testing showed, when using CLPs for the adhesion, the stress improved ca. 10 and strain ca. 6 times compared to polymeric lignin. For the β-casein NPs the values were 20 and 8, respectively, and for the β-casein coated CLPs between these two cases. When NPs were dispersed in adhesive formulation, the Young's moduli confirmed significant improvement in the elasticity of the joints over the adhesive alone. Exploitation lignin in nanoparticulate morphology is a potential method to prepare bionanomaterials for advanced applications.

In this systematic survey, an overview of non-conventional and soft-actuators is presented. The review is performed by using well-defined performance criteria with a direction to identify the exemplary applications in robotics. In addition to this, initial guidelines to measure the performance and applicability of soft actuators are provided. The meta-analysis is restricted to four main types of soft actuators: shape memory alloys (SMA), fluidic elastomer actuators (FEA), dielectric electro-activated polymers (DEAP) and shape morphing polymers (SMP). In exploring and comparing the capabilities of these actuators, the focus was on seven different aspects: compliance, topology, scalability-complexity, energy efficiency, operation range, performance and technological readiness level. The overview presented here provides a state-of-the-art summary of the advancements and can help researchers to select the most convenient soft actuators using the comprehensive comparison of the performance criteria.

Laminate structures composed of stiff plates and thin soft interlayers are widely used in aerospace, automotive and civil engineering encouraging the development of reliable non-destructive strategies for their condition assessment. In the paper, elastodynamic behaviour of such laminate structures is investigated with emphasis on its application in ultrasonic based NDT and SHM for the identification of interlayer mechanical and interfacial contact properties. A particular attention is given to the practically important frequency range, in which the wavelength considerably exceeds the thickness of the film. Three layer model with spring-type boundary conditions employed for imperfect contact simulation is used for numerical investigation. Novel effective boundary conditions are derived via asymptotic expansion technique and used for analysis of the peculiar properties of elastic guided waves in considered laminates. It is revealed that the thin and soft film influences the behaviour of the laminate mainly via the effective stiffnesses being a combination of the elastic moduli of the film, its thickness and interface stiffnesses. To evaluate each of these parameters separately (or to figure out that the available experimental data are insufficient), a step-wise procedure employing the effective boundary conditions is proposed and tested versus the laser Doppler vibrometry data for Lamb waves in Aluminium/Polymer film/Alumunium structure. The possibility of using film-related thickness resonance frequencies to estimate the film properties and contact quality is also demonstrated. Additionally, the rich family of edge waves is also investigated, and the splitting of fundamental edge waves into pairs is revealed.

The aerospace industry develops prognosis and health management algorithms to ensure better safety on board. Particularly for in-flight controls where jamming is dreaded. For that, vibration signals are monitored to predict future defect occurrences. However, time series are not labeled according to severity level, and the user can only assess the system health from the data mining procedure. To that extent, we developed a clustering algorithm using a deep neural network core. We encoded the time series into pictures to be feed into an artificially trained neural network: U-NET. From the segmented output, one-dimensional information on cluster frontiers is extracted and filtered without any parameter selection. Then, a kernel density estimation finally transforms the signal into an empirical density. Ultimately, a Gaussian mixture model extracts the latter independent components. The method empowered us to reveal different degrees of severity faults in the studied data, with their respective likelihood without prior knowledge. We compared it to state-of-the-art machine learning algorithms. However, internal clustering results evaluation for time series is an open question. As state-of-the-art indexes were not producing relevant results, we built a new indicator to fulfill this task. We applied the whole method to an actuator consisting of an induction machine linked to a ball screw. This study lays the groundwork for future training of diagnosis and prognosis structures in the health management framework.

Dielectric elastomer actuators (DEAs) offer robust, high energy density solutions for soft robotics. The proposed end effector consists of three spring roll configuration DEAs, each acting as a robotic finger, using a 3M VHB-F9473PC adhesive membrane. The lateral force, bending angle and response time of the actuator are measured experimentally and compared with the predictions of an analytical model. The cylindrical actuator measures 70 mm in length and 15 mm in diameter and achieved a lateral force of 30 mN, a bending angle of 6.8 ° and a response time of ≈ 1 s. Spring roll configuration DEAs are shown to reduce the effects of viscoelasticity seen in the membrane, making the actuator more controllable at higher voltages. The dielectric constant of the membrane is shown to be a limiting factor of actuation, with a decrease in dielectric constant resulting in larger actuation. The end effector successfully gripped numerous light objects for extended periods, showing the applicability of spring roll DEAs for soft end effectors.

Quantum squeezing, an intriguing phenomenon that amplifies the uncertainty of one variable while diminishing that of its conjugate, may be studied as a time-dependent process, with exact solutions frequently derived from frameworks grounded in adiabatic invariants. Remarkably, we reveal that exact solutions can be ascertained in the presence of time-variant elastic forces, eschewing dependence on invariants or frozen eigenstates formalism. Delving into these solutions as an inverse problem unveils their direct connection to the design of elastic fields, responsible for inducing squeezing transformations onto canonical variables. Of particular note, the dynamic transformations under investigation belong to a class of gentle quantum operations, distinguished by their delicate manipulation of particles, thereby circumventing the abrupt energy surges commonplace in conventional control protocols.

Detection of human movement requires lightweight, flexible systems to detect mechanical parameters (like strain and pressure) not interfering with user activity, and that he/she can wear comfortably. In this work we address such multifaceted challenge with the development of smart garments for lower limb motion detection, like a textile kneepad and anklet in which soft sensors and readout electronics are embedded for detecting movement of the specific joint. Stretchable capacitive sensors with a three-electrode configuration are built combining conductive textiles and elastomeric layers, and distributed at knee and ankle. They show an excellent behavior in the ~30% strain range, hence the correlation between their responses and the optically tracked Euler angles is allowed for basic lower limb movements. Bending during knee flexion/extension is detected, and it is discriminated from any external contact by implementing in real time a low computational algorithm. The smart anklet is designed to address joint motion detection in and off the sagittal plane. In this work, ankle dorsi/plantar flexion, adduction/abduction, and rotation are retrieved. Both smart garments show a high accuracy in movement detection, with a RMSE less than 4° in the worst case.

Human rhabdomyosarcomas are rarely cured by surgical resection alone. This is also true for high grade soft tissue sarcomas in dogs. Dogs with spontaneous sarcoma are good models for clinical responses to new cancer therapies. Strategic combinations of immunotherapy and oncolytic virotherapy (OV) could improve treatment responses in canine and human cancer patients. To develop an appropriate combination of immunotherapy and OV for dogs with soft tissue sarcoma (STS), canine cancer cells were inoculated with myxoma viruses (MYXVs) and gene transcripts were quantified. Next, cytokine concentrations in canine cancer cells were altered to evaluate their effect on MYXV replication. These studies indicated that, as in murine and human cells, type I interferons (IFN) play an important role in limiting MYXV replication in canine cancer cells. To reduce type I IFN production during OV, oclacitinib (a JAK1 inhibitor) was administered twice daily to dogs for 14 days starting ~7 days prior to surgery. STS tumors were excised and MYXV deleted for serp2 (MYXV∆SERP2) was administered at the surgical site at two time points post-operatively to treat any remaining microscopic tumor cells. Tumor regrowth in dogs treated with OV was decreased relative to historical controls. However, regrowth was not further inhibited in patients given combination therapy.

Conducting related research is crucial since there are still many problems that need to be resolved in the research on soft robots in the areas of material selection, structure design and manufacture, and drive control. Soft manipulators, a subset of soft robots, are now a popular area of study for many researchers. In comparison to typical manipulators, soft manipulators feature a high degree of gripping flexibility and a basic morphological structure. They are composed of flexible materials. It has a wide range of potential applications in healthcare, rehabilitation, bionics, and detection, and it can compensate for the drawbacks of rigid manipulators in some use scenarios. A modular soft-body torsional gripping system is developed after a torsional and gripping actuator is conceived, constructed, and its performance is examined. The torsion actuator and the grasping actuator can be combined in the system in a modular fashion. With the help of RGB-D vision algorithms, this multi-modular setup makes it possible to combine soft actuators with various twisting degrees and achieve exact gripping. Through pneumatic control, the target object is precisely grasped and rotated at various angles, enabling rotation of the target object in three dimensions.

Background. Shoulder in CrossFit should have a balance between mobility and stability. Glenohumeral internal rotation deficit and posterior shoulder stiffness are risk factors for overhead shoulder injury. Objective. To determine the effectiveness of instrument assisted soft tissue mobilization and horizontal adduction stretch in CrossFit practitioners’ shoulders. Methods: Twenty-one regular CrossFitters were allocated to experimental (stretching with isometric contraction and instrument assisted soft tissue mobilization) or control group (instrument assisted soft tissue mobilization). Each session lasted 5 minutes, 2 days a week, over a period of 4 weeks. Shoulder internal rotation and horizontal adduction (digital inclinometer), and posterior shoulder stretch perception (Park scale) were evaluated. Shapiro-Wilk test was used to analyze the distribution of the sample. Parametric student's t-test was used to obtain the intragroup differences. The inter- and intra-rater differences were calculated using a repeated measures ANOVA. Results. Changes were found in the experimental group following intervention (p < 0.05), and when comparing baseline and follow-up assessments (p < .05) in all variables. Significant differences were found in the control group following intervention (p < 0.05), in right horizontal adduction and left internal rotation. When comparing perception of internal rotation and horizontal adduction in both groups in the three assessments significant differences were found. Conclusions. Instrument assisted soft tissue mobilization can improve shoulder horizontal adduction and internal rotation. An instrument-assisted soft tissue mobilization technique yields the same results alone as those achieved in combination with post-isometric stretch with shoulder adduction.

This study aims to elucidate a soft computing approach for quantitative assessment of the scoring grade or rubrics for students in an outcome based education system. The intended approach resorts to a fuzzy membership based assessment of the different parameters of the scoring system, thereby yielding a novel and humanly assessment technique. The selection of the membership functions is based on the human behavior so as to make a realistic representation of the scoring strategy. The novelty of the proposed strategy lies in assigning fuzzy membership based weighted scores instead of simply assigning score bands to rubric categories, as is performed in normal rubrics based assessment. Comparative results demonstrated on a case study of Indian education scenario reveal the effectiveness of the proposed strategy over other fuzzy membership and normal rubrics based assessment procedures.

Orbital fractures are a common finding in facial trauma and serious complications may arise when orbital reconstruction is not done properly. The virtual planning can be used to manufacture patient-specific titanium orbital implants (PSI) through the process of selective laser melting. This method is currently considered the most accurate technique for orbital reconstruction. Even with the most accurate tehniques of bone reconstruction, there are still situations where enophthalmos is present after reconstruction which may be produced by intraorbital soft tissue atrophy. The aim of this paper was to evaluate the orbital soft tissue after postraumatic reconstruction of the orbital walls fractures. 10 patients diagnosed with unilateral orbital fractures were included in this study. A CT scan of the head region with thin slices (0.6mm) and soft and bone tissue windows was done. After data processing, the STL files were exported and the intraorbital fat tissue volume and the muscular tissue volume were masured. The volumes of affected orbit tissues were compared with the volumes of the healthy orbit tissues for each patient. Our findings conclude that a higher or a lower grade of fat and muscular tissue loss is present in all cases of reconstructed orbital fractures.

A better understanding of diseases progress in tissues vest on the accurate understanding of tissues under mechanical loading. Also, development of therapies for injuries may depend on the available mechanical data for soft tissues. In this study, the raw data of biaxial tensile testing of sclera soft tissue is presented in this paper. Biaxial mechanical testing of soft tissues presents details understanding of how soft tissues behave when compared to uniaxial testing. Biomechanical properties of soft tissues are vital in the development of accurate computational models. Reliable computational models of studying mechanisms of diseases depends mainly on the accurate and more details mechanical behavior of soft tissues. These accurate and detailed computational models may be utilized to further develop the understanding and therapies of various diseases. The mechanical tensile testing was conducted on the passive sheep sclera. Engineering stress vs strain of several samples of the sheep sclera are further presented determined from force and displacement experimental data. The goal of this paper is to make available biaxial data of sheep sclera soft tissue that can be further utilized.

A real-time two-way direct load control (TWDLC) of central air-conditioning chillers in wide area is proposed to provide demand response. The proposed TWDLC scheme is designed to optimize the load shedding ratio of every customer under control to ensure the target load to be shed is met at every scheduling period. In order to overcome the load reduction uncertainties of TWDLC, an innovative solution is proposed by applying a certain degree of loosening on the constraint of the actual shed load. Fuzzy linear programming is utilized to solve the optimization problem with fuzzy constraints. The proposed fuzzy linear programming problem is solved by delicately transforming it into a regular liner programming problem. A selection scheme used to obtain the feasible candidates set for load shedding at every sampling interval of TWDLC is also designed along with the fuzzy linear programming.

In this paper, a recent meta-heuristic optimization algorithm called the discrete-continuous hyper-spherical search algorithm is used to solve the mixed-integer nonlinear problem of soft open points (SOPs) and renewable distributed generators allocation along with new network reconfiguration methodology under different loading conditions to minimize the total power loss in balanced distribution systems. Multi-scenario studies, which aim to improve the investigation of the overall performance of the strategies, are conducted on IEEE 33-node and 83-node balanced distribution systems. The contributions of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to the system, are investigated to determine the real benefits gained from their allocation. The results obtained validate, with proper justifications, the effectiveness of allocating both SOPs and renewable distributed generators with the proposed network reconfiguration methodology to provide the best operation of distribution networks with minimum losses and enhanced power quality performance. It was also shown that SOPs successfully assist the growing integration plans of the renewable distributed generators units and can address issues related to voltage violations and network losses efficiently.

In this study, we investigate the magnetization behavior of coaxial nanowires fabricated through the sol-gel electrospinning method. Our analysis uncovers a significant reduction in coercivity for CoFe2O4 nanowires when BaTiO3 is used as the shell material, effectively transforming them from hard to soft magnetic. This intriguing behavior is attributed to the magnetization reversal effect at the interface between ferromagnetic and paramagnetic regions, and it is also observed in NiFe2O4 and Fe2O3 nanowires. Surprisingly, introducing a GdBa2Cu3O7 shell induces a similar effect. Additionally, we employ magnetic impedance measurements on the coaxial nanowires, unveiling their potential for magnetic field sensing applications.

Soft drinks exist in various forms and brands and are marketed by different brewery industries across the country. Nigeria been an underdeveloped country were aforesaid health problems are common, people tends to consume them lots believing it gives more energy. This study was therefore set to assess the sugar content from different soft drinks sold in Nigeria. Ten (10) soft drinks registered and licensed in Nigeria by their respective companies were purchased from a supermarket in Ihumudumu environment of Ekpoma, Nigeria. The sugar contents were assessed using standard methods. Result showed significant differences (p<0.05) in ranges of 0.36g/100ml (Limca) to 3.88g/100ml (Teem Bitter Lemon). Conclusively, the sugar contents were all below recommended value and it can be consumed by those who need low sugar in the body.

In this study, we present the concept of interval-valued fuzzy soft point and then introduce the notions of neighborhood and quasi-neighbourhood of it in interval-valued fuzzy soft topological spaces. Separation axioms in interval-valued fuzzy soft topology, so-called $q$-$T_{i}$ for $ i=0,1,2,3,4 ,$ is introduced and some of its basic properties are also studied.

The structural evolution and phase composition of multi-block thermoplastic polyurethanes, with different nature of the soft segments based on poly(butylene adipate) (PBA), were analyzed during in-situ thermal treatments. A combination of synchrotron small- and wide-angle X-ray scattering, differential scanning calorimetry, thermogravimetric analysis, and FTIR spectroscopy was used to determine the influence of macrodiol nature and crystallization conditions on the polymorphic behavior of PBA. Using a new synthesis scheme, a relatively high degree of crystallinity for urethane blocks was achieved, which depends on the diisocyanate type in the structure of the soft segment. The hard segment domains impose geometrical constraints on PBA, thereby altering its crystallization process compared to the neat oligomer. Thus, crystallization after annealing at a low temperature (80 °C) is fast, predominantly yielding a metastable β-phase. When heated to 180 °C, which is higher than the hard-segment melting temperature, a phase-separated structure is observed. Subsequent crystallization is slower, favoring the formation of the stable α-PBA modification. The phase separation can be observed even after the hard block melting. A notably slow crystallization from an isotropic melt was documented after the disruption of phase separation at 230 °C.

In this paper, chaos sequence is used to replace the traditional Spread Spectrum sequence. From the perspective of the communication partner, a new method of generating the initial value of chaotic sequence is proposed, which is more suitable for the multi-base Spread Spectrum System and easy to extract. In order to further improve the error performance of the system and ensure the integrity of the system, an improved suboptimal soft information extraction method based on log-likelihood ratio (LLR) is proposed in the channel coding module, which can further improve the error performance of the system. On this basis, we choose the synchronization mode of multiple transmission of one reference signal to solve the problem that chaotic sequence is difficult to obtain synchronization because of its aperiodic characteristics. Finally, the system is simulated in the channel with low SNR. The simulation results show that chaotic sequence as Spread Spectrum code can make the signal transmit accurately in the worse channel environment. The performance gain of applying soft information decoding decision in the M-ary Spread Spectrum System with chaotic sequence as Spread Spectrum code can reach 5.2dB compared with the traditional Direct Spread Spectrum System.

Software engineering is a comprehensive process that requires developers and team members to collaborate across multiple tasks. In software testing, bug triaging is a tedious and time-consuming process. Assigning bugs to the appropriate developers can save time and maintain their motivation. However, without knowledge about a bug's class, triaging is difficult. Motivated by this challenge, this paper focuses on the problem of assigning the suitable developer to new bug by analyzing the history of developers’ profiles and analyzing history of bugs for all developers using machine learning-based recommender systems. Explainable AI (XAI) is AI that humans can understand. It contrasts with "black box" AI, which even its designers can't explain. By providing appropriate explanations for results, users can better comprehend the underlying insight behind the outcomes, boosting the recommender system's effectiveness, transparency, and confidence. In this paper, we propose two explainable models for recommendation. The first one is an explainable recommender model for personalized developers generated from bug history to know what the preferred type of bug is for each developer. The second model is an explainable recommender model based on bugs to generate the best developer for each bug from bug history.

Since the first description of bisphosphonate-related osteonecrosis of the jaw (BRONJ) numerous research groups have focused on possible pathological mechanisms including the suppression of the bone turnover of the jaw, antiangiogenic effects and soft tissue toxicity. In our review we focused on summarizing the role of the soft tissues in the development and progression of BRONJ. The biological behavior of fibroblasts can be significantly influenced by bisphosphonates (BP) such as a concentration dependent reduction of cell viability. High concentrations of BP can induce apoptosis and necrosis of the cells. Comparable effects could be detected for keratinocytes. Compared to non-nitrogen containing bisphosphonates nitrogen-containing BP have worse effects on cell biology by blocking the mevalonate pathway. Next to this the cell architecture and the expression levels of several genes and proteins are significantly disturbed by BP. These inhibitory effects of BP are in accordance with BP related reduced angiogenesis and neovascularization and could underline the hypothesis that inhibition of fibroblasts and keratinocytes results in delayed wound healing and can induce and trigger BRONJ.

Fifteen new diterpenoids, namely xishaklyanes A-O (1-15), along with three known related ones (16-18), were isolated from the soft coral Klyxum molle collected from Xisha Islands, South China Sea. The stereochemistry of the new compounds were elucidated by a combination of detailed spectroscopic analyses, chemical syntheses, quantum chemical calculations and comparison with the reported data. The absolute configuration of compound 18 was established by the modified Mosher's method for the first time. In bioassay, some of these compounds exhibited considerable antibacterial activities on fish pathogenic bacteria, and compound 4 showed the most effective activity with MIC of 0.225 g/mL against Lactococcus garvieae.

The increasing trend of studying the innate softness of robotic structures and amalgamating it with the benefits of the extensive developments in the field of embodied intelligence has led to sprouting of a relatively new yet extremely rewarding sphere of technology. The fusion of current deep reinforcement algorithms with physical advantages of a soft bio-inspired structure certainly directs us to a fruitful prospect of designing completely self-sufficient agents that are capable of learning from observations collected from their environment to achieve a task they have been assigned. For soft robotics structure possessing countless degrees of freedom, it is often not easy (something not even possible) to formulate mathematical constraints necessary for training a deep reinforcement learning (DRL) agent for the task in hand, hence, we resolve to imitation learning techniques due to ease of manually performing such tasks like manipulation that could be comfortably mimicked by our agent. Deploying current imitation learning algorithms on soft robotic systems have been observed to provide satisfactory results but there are still challenges in doing so. This review article thus posits an overview of various such algorithms along with instances of them being applied to real world scenarios and yielding state-of-the-art results followed by brief descriptions on various pristine branches of DRL research that may be centers of future research in this field of interest.

The aim of this article is introduced the concept of double framed T-soft fuzzy set (DFT-soft fuzzy set) which is the combination of soft set and fuzzy set. We also defined the notions and apply this concept in BCK/BCI-algebras. By using example, we also discussed the concept of double framed T-soft fuzzy algebra (DFT-soft fuzzy algebra) and double framed B-soft fuzzy algebra (DFB-soft fuzzy algebra) and also investigated their properties. Each double framed T-soft fuzzy algebra is double framed B-soft fuzzy algebra but by using example, we proved that converse may or may not be possible.

Five new cembrane-type diterpenes, lobocalines A–E (1–5), and four new steroids, lobocalines F–I (9–12), along with six known related compounds (6–8 and 13–15) were isolated from the Yalong Bay soft coral Lobophytum catalai. The structures of the new compounds were elucidated by extensive spectroscopic analysis, NMR calculation with DP4+ analysis, time-dependent density functional theory-electronic circular dichroism (TDDFT-ECD) calculations, X-ray diffraction analyses, and the comparison with the reported spectroscopic data of known compounds. Further, with the aid of X-ray diffraction analysis, the structure of lobocrasol B (15) was firmly revised as 15a. In in vitro bioassays, compound 2 showed moderate antibacterial activities against fish pathogenic bacteria Streptococcus parauberis KSP28 and Phoyobacterium damselae FP2244 with minimum inhibitory concentration (MIC) values of 8.7 and 17.3 µg/mL, respectively. All the steroids exhibited antibacterial activities against the S. parauberis KSP28 with MIC values ranging from 12.3 to 53.6 µg/mL. Compounds 2, 7 and 14 have remarkable inhibitory effects on the hemolysin production of Staphylococcus aureus, while compounds 8–12 have medium inhibitory effects on the pyocyanin production in Pseudomonas aeruginosa.

In this study, the motion characteristics of soft alginate microrobots were investigated with wireless magnetic fields in complex fluidic environments. Our aim is to explore the various motion modes that arise as a result of shear forces in viscoelastic fluids. Polyacrylamide (PAA), a water-soluble polymer, was characterized to produce a dynamic environment with a non-Newtonian fluid. The robots were fabricated by an extrusion-based microcentrifugal droplet method. We successfully demonstrated the feasibility of both wiggling and tumbling motions using snowman-shaped microbots. It is found that wiggling motion is primarily influenced by the interaction between the viscoelastic fluid environment and the non-uniform magnetization of the microbots. Additionally, it is discovered that modifying the viscoelasticity properties of the fluid can affect the motion behavior of the microbots. Furthermore, we observed that swarms of microbots exhibit non-uniform behavior within complex environments. Our velocity analysis has provided valuable insights into the relationship between applied magnetic fields and motion characteristics, enabling a more realistic understanding of surface locomotion in the context of targeted drug delivery.

An attractive option for realizing applications in radiation environments is to employ All-Programmable System-on-Chips (APSoCs) thanks to their high-performance computing and power efficiency merits. Despite APSoC's advantages, like any other electronic device, they are prone to radiation effects. Processors found in APSoCs must, therefore, be adequately hardened against ionizing-radiation to become a viable alternative for harsh environments. This paper proposes a novel triple-core lockstep (TCLS) approach to secure the Xilinx Zynq-7000 APSoC dual-core ARM Cortex-A9 processor against radiation-induced soft errors by coupling it with a MicroBlaze TMR subsystem in Zynq's programmable logic (PL) layer. The proposed strategy uses software-level checkpointing principles along with roll-back and roll-forward mechanisms (i.e. software redundancy), and hardware-level processor replication as well as checker circuits (i.e. hardware redundancy). Results of fault injection experiments show that the proposed solution achieved high soft error security by mitigating about 99% of bit-flips injected into both ARM cores' register data.

In this paper we evaluate the effects of hard and soft constraints on the Iterative Data Snooping (IDS), an iterative outlier elimination procedure. Here, the measurements of a levelling geodetic network were classified according to the local redundancy and maximum absolute correlation between the outlier test statistics, referred to as clusters. We highlight that the larger the relaxation of the constraints, the higher the sensitivity indicators MDB (Minimal Detectable Bias) and MIB (Minimal Identifiable Bias) for both the clustering of measurements and the clustering of constraints. There are circumstances that increase the family-wise error rate (FWE) of the test statistics, increase the performance of the IDS. Under a scenario of soft constraints, one should set out at least three soft constraints in order to identify an outlier in the constraints. In general, hard constraints should be used in the stage of pre-processing data for the purpose of identifying and removing possible outlying measurements. In that process, one should opt to set out the redundant hard constraints. After identifying and removing possible outliers, the soft constraints should be employed to propagate their uncertainties to the model parameters during the process of least-squares estimation.

Background: Skin and soft tissue infections (SSTI) are common presentations to the emergency department. However, this is less common after contact with contaminated water, both salt or fresh. This review presents the diagnosis and the management of water-related soft tissue sepsis in this vulnerable and difficult to treat subgroup of necrotizing soft tissue sepsis. Methods: A summative literature overview regarding bacterial and fungal SSTI after contact with contaminated water, with practical diagnostic and management aspects addressed. Results: The literature indicates that these remain difficult to treat wounds and organisms. An approach using appropriate diagnostic tools with both medical and surgical management strategies is provided. Conclusion: SSTI due to water contamination of wounds involve unusual organisms with unusual resistance patterns and require a nuanced and directed diagnostic approach with adaptation of the normal antibiotic or antifungal selection to achieve cure, along with aggressive debridement and wound care.

Background: PRAME, NY-ESO-1 and SSX2 are cancer testis antigens (CTAs), which in normal tissues are expressed in testicular germ cells with re-expression in numerous cancer types. Their ability to elicit humoral and cellular immune responses have rendered them promising targets for cancer immunotherapy, but they have never been studied in a large and well-characterized cohort soft tissue sarcomas (STS). Methods: On protein level, we examined PRAME, NY-ESO-1 and SSX2 expression in tumour tissues of 249 STS using immunohistochemistry. We correlated expression levels with clinicopathological parameters including Tumour-infiltrating lymphocyte (TIL) counts, grading and long- term survival. Results: Expression of PRAME, NY-ESO-1 and SSX2 was observed in 25 (10%), 19 (8%), and 11 (4%) of 249 specimens with distinct patterns for histo subtypes. Expression of PRAME was associated with shorter patient survival (p=0.005) and higher grade (G2 vs G3, p=0.001) while NY-ESO-1 expression was correlated with more favourable survival (p=0.037) and low grade (G2 vs G3, p=0.029). Both PRAME and NY-ESO-1 expression was more frequent in STS with low TILs counts. Conclusions: CTAs PRAME, NY-ESO-1 and SSX2 show distinct expression patterns in different STS subtypes. These results may guide future immunotherapeutic approaches in STS.

This article, based on network science, aims to contribute to overcoming its geometric and technological phases. The novelty consists in considering links of networks as linked by superimposed networks, termed here multiple superimposed soft networks (MSSN), which is introduced as a research issue. Such links of links (termed here as passive links) concern, for instance, correspondences, incompatibilities, and temporal synchronizations between the occurrences of pairs of active links of effective networks, such as those based on electrical and telecommunication. A possible constitutive mechanism of such passive linkage consists of linkage representations for practices and histories of use expressed by their validating statistical reoccurrences. We consider the possible emergent nature of the passive linkage. The reason for introducing the design and usage of MSSN properties as a research issue involves making new approaches to profile and manage networks available. Correspondence between active linkage and MSSN properties should be a matter for an experiential, machine-learning approach. Research issues relate their possible usage on the active linkage such as for classification, comparations, detection of criticalities, diagnosis, performance evaluation, and regulatory as weak forces. Furthermore, the possible identification of standard corresponding configurations of passive and active linkage are finalized to avoid their establishment or, conversely, in facilitating their establishment and keeping their replication in different contexts (or partially and in combinations) and identifying related standardized approaches (also for classes of configurations having significant levels of equivalence). This research project has methodological generalizing aspects of trans-disciplinarity. We conclude by mentioning related research issues.

This study investigates the impact of narrow-band terahertz pulses on the ferroelectric order parameter in Ba0.8Sr0.2TiO3 films on various substrates. The 375 nm thick BST film on an MgO (001) substrate exhibits enhanced THz-induced second harmonic generation when excited by THz pulses with a central frequency of 1.6 THz, due to the resonant excitation of the soft phonon mode. Conversely, the BST film on a Si (001) substrate shows no enhancement, due to its polycrystalline state. The 800 nm thick BST film on an MgO (111) substrate demonstrates maximum of second harmonic generation signal when excited by THz pulses at 1.8 THz, that is also very close to it`s soft mode frequency (1.9 THz). Notably, the frequency spectrum of the BST/MgO (111) film reveals peaks at both the fundamental and doubled frequencies, highlighting the quadratic dependence of SHG intensity on the THz pulse's electric field strength.

Dynamic sparse training is an effective strategy to alleviate the training and inference demands of artificial neural networks. However, current sparse training methods face a challenge in achieving high levels of sparsity while maintaining performance comparable to that of their fully connected counterparts. The Cannistraci-Hebb training (CHT) method produces an ultra-sparse advantage compared to fully connected training in various tasks by using a gradient-free link regrowth method, which relies solely on the network topology. However, its rigid selection based on link prediction scores may lead to epitopological local minima, especially at the beginning of the training process when the network topology might be noisy and unreliable. In this article, we introduce the Cannistraci-Hebb training soft rule (CHTs), which applies a flexible approach to both the removal and regrowth of links during training, fostering a balance between exploring and exploiting network topology. Additionally, we investigate the network topology initialization using several approaches, including the bipartite scale-free and bipartite small-world network models. Empirical results show that CHTs can surpass the performance of fully connected networks with MLP architecture by using only 1% of the connections (99% sparsity) on the MNIST, EMNIST, and Fashion MNIST datasets and can provide remarkable results with only 0.1% of the links (99.9% sparsity). In some MLPs for image classification tasks, CHTs can reduce the active neuron network size to 20% of the original nodes (neurons), demonstrating a remarkable ability to generalize better than fully connected architectures, reducing the entire model size. This represents a relevant result for dynamic sparse training. Finally, we present evidence from larger network models such as Transformers, with 10% of the connections (90% sparsity), where CHTs outperform other prevalent dynamic sparse training methods in machine translation tasks.

: Clay covers a substantial portion of the Earth. Such soil covers Iraq’s central and southern regions, where the depth of the clay may reach 150 m. All enhancement techniques and methods for transporting large loads cease to function or become prohibitively expensive in such soils. In this case, thermal treatment is the most effective method. In this study, a novel heating system was created and produced utilizing gas as the heat source via boreholes that simulate reality. The borehole heating cases were planted inside soft clay soil to enhance the soil. Different parameters were investigated, including the spacing between boreholes (3, 4, and 5 times the outer diameter of the borehole), the heating depth (1, 1.5, 2, and 2.5 times the width of the model footing), the duration of heating (2, 4, 6, 8, and 10 hrs), and the pattern (square, circular, triangular). The results showed the strength and behavior of the soil treated with heated boreholes at varying spacings, depths, patterns, and heating periods. The best results were found for a spacing, depth, and heating time of three times the outer diameter of the borehole, two times the width of the footing model, and eight hours, respectively. The effect of the heated borehole casing pattern was small when the heated borehole casing was used. The experiments conducted on heated soil showed that the undrained shear strength (Cu) increased from 14 to 360 kPa and then dropped to 140 kPa (as an average with depth). In contrast, the average angle of internal friction (Ø) rose from 0 to 52 degrees and decreased to 16 degrees (as an average with depth) from the center of the heating model to the furthest point affected by heating. In addition, the EDS pattern showed that components like silicon, aluminum, and iron dropped at 300 °C and rose at 400 °C in the treated soils. At 200 °C, the calcium content rose, and then dropped dramatically at 400 °C. The carbon percentage increased at 300 °C and decreased at 400 °C. The elements’ proportions showed little change or remained stable at temperatures between 400 °C and 600 °C.

Three new cembranoids (1–3) and a new casbanoid (4), along with three known analogues (5–7), have been isolated from the soft coral Sinularia nanolobata collected off Ximao Island. The structures including the absolute configurations of new compounds were established by extensive spectro-scopic data analysis, time-dependent density functional theory/electronic circular dichroism (TDDFT-ECD) calculations and the comparison with spectroscopic data of known compounds. In in vitro bioassay, compounds 1 and 5 exhibited moderate cytotoxic activities against human erythroleukemia (HEL) cells line with IC50 values of 37.1 and 42.4 uM, respectively.

Poor interlaminar fracture toughness has been a major issue in glass fiber-reinforced epoxy resin (GF/EP) laminate composites. In this paper, soft carboxy-terminated liquid nitrile (CTBN) rubber particles and rigid nano-SiO2 are used to toughen the epoxy resin (EP) matrix to improve the interlayer properties of GF/EP laminate composites. The effects of adding two toughening agents on the mechanical and interlayer properties of GF/EP laminates were studied. The results showed that adding the two kinds of particles improved the mechanical properties of the epoxy matrix. When the additional amount of flexible CTBN rubber particles was 8wt%, and the rigid nano SiO2 was 0.5wt%, the fracture toughness of the matrix resin was increased by 215.8%, and the tensile strength was only decreased by 2.3% compared with the pure epoxy resin. On this basis, the effects of two kinds of particles on the interlayer properties of GF/EP composites were studied. Compared with the unmodified GF/EP laminates, the interlayer shear strength and mode Ⅰ interlayer fracture toughness is significantly improved by toughening agent, and the energy release rate GIC of interlayer shear strength and interlayer fracture toughness is increased by 109.2%, and 86.8%, respectively.

Agricultural production needs technologies that assist the management of natural resources, for example, the collection of real-time data on soil, water, weather, crops, and biodiversity conditions. Sensor technology solutions and open-source software are appropriate for promoting more sustainable agricultural production. Among the advantages of using open-source technologies and software is its potential for extension, collaboration, customization, flexibility, maintenance cost, transparency, speed, and better security. Given the above, the objective of this research was to find, in different electronic databases, exclusively open-source software for precision agriculture, offering a systematic review, and addressing considerations and challenges. This survey considers up-to-date open-source software available in repositories such as GitHub and GitLab, to understand its characteristics and application formats.

The development of novel coherent and brilliant sources, such as soft X-ray Free Electron Laser (FEL) and High Harmonic Generation (HHG) enables new ultrafast analysis of the electronic and structural dynamics of a wide variety of materials. Soft X-ray FEL delivers high brilliance beams with short pulse duration, high spatial coherence and photon energy tunability. In com-parison with FELs, HHG X-ray sources are characterized by a wide spectral bandwidth and few to sub-femtosecond pulses. The approach will lead to time-resolved reconstruction of molecular dynamics, shedding light on different photochemical pathways. The high peak brilliance of soft X-ray FELs facilitates investigations in nonlinear regime, while the broader spectral bandwidth of the HHG sources may provide the simultaneous probing of multiple components. Significant technical breakthroughs in these novel sources are under way to improve brilliance, pulse dura-tion, and to control spectral bandwidth, spot size, and energy resolution. Therefore, in the next few years, the new generation of soft X-ray sources combined with novel experimental tech-niques, new detectors, and computing capabilities will allow the study of several extremely-fast dynamics, such as vibronic dynamics. In the present review, we shortly discuss recent devel-opments in experiments, performed with soft X-ray FELs and HHG sources, operating near car-bon K-absorption edge, being a key atomic component in biosystems and soft materials. Differ-ent spectroscopy methods such as time-resolved pump-probe techniques, nonlinear spectrosco-pies and photoelectron spectroscopy studies have been addressed in an attempt of a better un-derstanding of fundamental physico-chemical processes

This paper presents a comparative analysis of the ZVZCS soft switching technique with the ZVS and the ZCS counterpart. The generalization of the voltage-current crossover or the energy loss factor obtained from simulation of the prototype converter shows that the ZVZCS significantly reduces the loss and helps to improve the efficiency of the converter as compared to the ZVS or the ZCS. On the other hand, it is also found that the soft switching range of operation of the ZVS and the ZCS are largely affected by the maximum switch voltage and switch current respectively. In contrary, these factors have a negligible effect on the ZVZCS operation which results in an extended range of soft switching operation. Additionally, a detailed LTPICE simulation is performed for selected ZVS, ZCS and ZVSCS topologies from the recent literature and the switching losses in the main switches of the converters are measured. It is observed that the energy losses in the ZVZCS mode are reduced on average by approximately 26 % at turn on and 20 % at the turn off as compared to the ZVS and the ZCS. Besides, the low standard deviation in this mode confirms a stable low loss profile which renders extended soft switching range. An experimental test is also conducted by building the prototype converter to verify the simulation results. It is found that the switching losses are minimum while the converter is operated in the ZVZCS mode. Besides, the efficiency drop remains consistently low as compared to the ZVS and the ZCS in the whole operating range. Resultantly, the simulation and the experimental results are both found to be consistent.

Comprehensively understanding the spatial ecology and habitat preferences of endangered species is essential for population restoration and conservation. We investigated the home range and movement of the endangered Amur soft-shell turtle (Pelodiscus maackii) in the Ussuri River, Heilongjiang Province, Northeastern China. The study involved tracking 19 Amur soft-shell turtles from late June to mid-October, 2022, resulting in complete and partial home range size data for eight subadults and two adults, respectively. The primary analysis focused on eight subadults, and the models that best described daily movement were identified. We also explored the potential factors influencing home range size. Mean movement rate ranged from 39.18 ± 20.04 m to 72.45 ± 29.36 m and was positively correlated with the linear home range and water temperature. The most insightful home range estimate was a 95% kernel density estimate, employing likelihood cross-validation smoothing with constraints set to the river boundaries. The mean home range size was 1.02 ha and was not correlated with body size. Subadults tended to establish well-defined home ranges over time; whereas, defining home ranges for adults proved challenging. This research addresses a gap regarding the ecology of the Amur soft-shell turtle and provides a foundation for future conservation plans.

The stability of deep soft rock tunnels is of particular concern under seepage conditions. Aiming at thoroughly discussing the seepage actions and their consequences on the support scheme of such structures, the host rocks of the Weilai Tunnel situated in Guangxi province of China are taken as the research substance. Emphasizing on seepage conditions, stresses, displacements and plastic zone radii along the surrounding rocks of such tunnel are adequately examined taking into consideration the Mogi-Coulomb strain criterion and the elastic-plastic theory. Subsequently, based on strain-softening model, the coupled actions of seepage and softening on the rocks surrounding the tunnel are studied. According to the results, it is revealed that the support scheme of deep soft rock tunnels must be of highest resistance possible to better decrease the plastic zone and the tangential stress along the host rocks. Moreover, throughout the surrounding rocks, the dissemination of pore water pressure is strongly affected by the uneven permeability coefficient under anisotropic seepage states. Combined effects of softening and seepage are very dangerous for the surrounding rocks of deep-buried tunnels. To better guarantee reasonable longevity of such tunnels, long-term monitoring of their support structures with reliable remote sensors is strongly recommended.

The extent of micro-phase separation in polyurethanes (PUs) depended on the molecular weight, the chemical nature and the structure of the polyol/soft segments. Balanced properties in PUs were obtained by using blends of polyols during synthesis. No previous studies have been devoted to understand the interactions between the soft segments that affect the properties of the PUs. In this study, different blends of two polyols of different nature (polyester – PE - and polycarbonate diol - CD) and similar molecular weight were prepared and their structural, thermal, surface, viscoelastic and self-adhesion properties were assessed. PE showed larger number of structural repeating units and higher number of polar groups than CD, but the carbonate-carbonate interactions in CD were stronger than the ester-ester interactions in PE. The blending of CD and PE imparted synergic structural properties, particularly in the ones containing less than 50 % PE, they were associated to the disrupt of carbonate-carbonate interactions in CD and the formation of new ester-carbonate and hydroxyl-carbonate interactions. Therefore, higher glass transition temperatures, a new diffraction peak at 2θ = 24°, one additional thermal degradation at 426-436 °C, and less steeper decline of the storage moduli to lower temperature were found in CD+PE blends with less than 50 wt.% PE. Furthermore, the different interactions between the polyol chains in the blends were also evidenced on their surface properties, and all CD+PE blends showed self-adhesion property which seemed related to the existence of ester-carbonate and carbonate-carbonate interactions.

Fungi of the genus Aspergillus are widespread in the environment where they produce large quantities of airborne conidia. Inhalation of Aspergillus spp. conidia in immunocompromised individuals can cause a wide spectrum of diseases, ranging from hypersensitivity responses to lethal invasive infections. Upon deposition in the lung epithelial surface, conidia encounter and interact with complex microbial communities that constitute the lung microbiota. The lung microbiota has been suggested to influence the establishment and growth of Aspergillus spp. in the human airways. However, the mechanisms underlying this interaction have not yet been sufficiently investigated. In this study, we aimed to evaluate the presence of commensal bacteria antagonistic to Aspergillus in the lung. To this end, we enriched and isolated bacterial strains able to inhibit the germination of conidia from bronchoalveolar lavage fluid (BALF) samples of lung transplant recipients. We used a novel enrichment method based on a soft agar overlay plate assay in which bacteria are directly in contact with conidia and for which inhibition can be readily observed during enrichment. We isolated a total of five bacterial strains, identified as Pseudomonas aeruginosa, and able to inhibit the germination and growth of Aspergillus fumigatus in a soft agar confrontation assay, as well as in a high-throughput multiplate assay. Moreover, we also showed a strong inhibition of A. fumigatus growth on Calu-3 cell culture monolayers. However, the isolated P. aeruginosa strains were shown to cause significant damage to the cell monolayers. Overall, we validated this novel one-step enrichment approach for the isolation of bacterial strains antagonistic to A. fumigatus from BALF samples. This opens up a new venue for targeted enrichment of antagonistic bacterial strains against specific fungal pathogens.

The aim of the following paper was to determine the influence of soft tissue therapy on respiratory efficiency and chest mobility of women suffering from breast cancer. This study was a controlled randomized trial. Tests were carried out in a group of patients (n=49), who were hospitalized in the Province Polyclinic Hospital, Konin, Poland. In the study group, irrespective of the standard physical therapy program, an additional therapy program was run. The program consisted in applying specific techniques of soft tissue treatment. All patients in the each term were subject to pulmonary function test, chest mobility and pain assessment. Statistical analysis of the obtained results of spirometry and chest mobility assessment have revealed no differences in the analyzed parameters between the examined groups in the period of joint therapeutic treatment. In the period between the 3rd examination and the end of the 11-month- rehabilitation treatment, statistically significant differences were observed in the analyzed spirometry parameters, however, there was no difference in the parameters describing airflow in small airways (MEF₅₀,PEF) between individual groups, during consecutive examinations in the course of diversified therapeutic treatment. Chest mobility assessment of the patients, performed during diversified therapeutic treatment, revealed statistically significant differences between the groups. However, there was no difference between the examined groups, as far as pain sensation is concerned. Enhancing the regular rehabilitation program by including additional therapeutic methods, which are based on myofascial release and post-isometric relaxation techniques, had a beneficial effects regarding respiratory system efficiency.

Alveolar soft part sarcoma (ASPS) is a rare mesenchymal neoplasm. It affects young adults more and occurs more frequently in the extremities. ASPS is exceedingly rare in the nasal cavity. We report a case of ASPS in the nasal cavity of a 17-year-old female. Its most striking features included organoid and pseudoalveolar arrangement of tumor cells, which were large and polygonal, with vesicular nuclei and abundant eosinophilic cytoplasm rich in granules. There were PAS-positive, diastase-resistant crystalline rods within the cytoplasm. Our case displayed inapparent pseudoalveolar growth pattern and frank pleomorphism. The diagnosis of ASPS, which presents uncommon morphologic findings in unusual sites, is challenging. Recognition of ASPS is greatly assisted by attention to its characteristic cytological features, including intracytoplasmic crystals and immunohistochemistry showing absence of skeletal muscle, epithelial, and neuroendocrine markers.

The aim of this study was to evaluate the biomechanical changes of the cornea after wearing soft contact lenses (CLs) in healthy myopic patients measured with the Corvis ST® analyzer. This prospective, cross-sectional, single-center study was performed in twenty-two Caucasian patients aged between 19 and 24 years (20.64 ± 1.21 years) range). Five device-specific biomechanical parameters, central corneal thickness and intraocular pressure were measured prior to fitting and one month after CLs wear. Differences between the means of the DA Ratio and the standard deviation of the DA Ratio pre- and post-CLs wear were found to be significant (p value=0.002 in both cases). Significant differences were found between pre- and post-CLs wear values in CCT (p value=0.013). For all other biomechanical measures, no significant differences were observed before and after treatment. A significant association was found between changes in bIOP and classification according to changes in Int. Radius (p value = 0.047) and SSI (p value = 0.026) standard deviations. The corneal biomechanical indices provided by CST demonstrate that fitting of soft CLs is a safe optical compensation method for the stability of corneal stiffness. No significant differences were found pre- and post-CLs wear in the assessment of bIOP.

Aiming at the problem that soft robots are challenging to take into account both flexibility and bearing capacity, Using the software Pneu-Net driver as the deformation mode, magnetorheological fluid material phase transformation to achieve variable stiffness, A pneumatic modular soft joint structure with dynamically adjustable deformation and stiffness in all directions is proposed. In this paper, mathematical models of deformation and variable stiffness are established. The correspondence between gas pressure and deformation and applied current and joint stiffness is obtained. The finite element analysis method was used to simulate the deformation characteristics and variable stiffness characteristics of modular joints based on the Yeoh model. Finally, the theoretical and simulation results are verified by deformation and variable stiffness tests. It is proved that the modular joint has good rigid-flexible coupling characteristics.

This paper describes a new optimization methodology of testing vector sets reduction for testing of soft-processor cores and their individual blocks. The deterministic test vectors both for whole core and its individual blocks are investigated that significantly reduce the testing time and amount of test data that needs to be stored on the tester memory. The processor executes an assembler program which together with determined testing vectors ex-ercise its functionality. The new BIST methodology applicable at industrial testing of processor cores, diagnostics and dynamic reconfiguration of FPGA is proposed. This novel methodology combined with dynamic reconfiguration of FPGAs can be profitable applied for missions-critical i.e. FPGAs operate in space, or other difficult condition where are explore on radiation. Experimental results demonstrate that the proposed approach reduces many times testing time.

This paper introduces a closed-loop control strategy for maintaining consistency of liquid temperature in commercial Drop on Demand (DoD) inkjet printing. No additional sensors or additional actuators are installed in the printhead while achieving the consistency in liquid temperature. To this end, this paper presents a novel in situ sensing-actuation policy at every individual liquid-nozzle, where the jetting mechanism has three distinct roles. It is used for jetting liquid droplet onto the print media based on the print-job. It is used as a soft sensor to estimate the real-time liquid temperature of the jetting nozzle. While not jetting liquid, it is used as a heating actuator to minimize the gradient of liquid temperature among nozzles. The soft sensing based in situ controller is implemented in an experimentally validated digital twin that models the thermo-fluidic processes of the printhead. The digital twin is scalable and flexible to incorporate an arbitrary number of liquid-nozzles, making the control strategy applicable for future designs of the printhead.

Work reviews the new isolated isolated cembranoid diterpene derivatives from species belonging to the family Alcyoniidae, which comprises the genera Sarcophyton, Sinularia, and Lobophytum as well as their biological properties, during 2016–2017. The compilation permitted to conclude that much more new cembranoid diterpenes were found in the soft corals of the genus Sarcophyton sp. (33 new compounds) than in those belonging to the genera Lobophytum (17) or Sinularia (8). Several methods have been used for identifying these new compounds, after extraction with organic solvents and fractionation. The fractions obtained, in some cases, were followed by TLC, and again subjected to chromatographic procedures, including semi-preparative HPLC. Beyond the chemical composition, the biological properties were also evaluated, namely anti-microbial against several Gram-positive and Gram-negative bacteria and fungi, anti-inflammatory and anti-tumoral against several types of cancer cells. Although the biological activities detected in almost all samples, they were not outstanding ones.

Skin and soft-tissue infections (SSTI) are common cases of hospital-acquired infections with aetiologic agents exhibiting antimicrobial resistance (AMR). We determined the prevalence, proportion of laboratory-investigated cases, AMR-profiles, and factors associated with SSTI and multi-drug resistance (MDR). This study was based on archived data of patients suspected of SSTI from 2019-2021 at Jinja Regional Referral Hospital. The analysis involved 268 randomly selected patient reports. Prevalence of SSTI was 66.4%. Laboratory-investigated cases were 14.11%. Staphylococcus aureus (n=51) was the most isolated organism. MDR pathogens explained 47% of infections. Methicillin-resistant S. aureus was up to 44%. In addition, 61% of Gram-negatives had the potential to produce extended-spectrum beta-lactamases, while 27% were non-susceptible to carbapenems. Ward of admission was significantly associated with infection (aPR=1.78, 95% CI: 1.003-3.18, p-value=0.04). Age category (19-35) was an independent predictor for MDR infections (aPR=2.30, 95%CI:1.02-5.23, p-value=0.04). The prevalence is relatively high with MDR pathogens responsible for almost half of the infections. Routine use of culture and sensitivity testing should be done for proper infection management. Gentamicin and ciprofloxacin can be considered for empirical management of emergency SSTI suspected of S. aureus. Recognizing SSTI under the Global Antimicrobial resistance Surveillance System would lead to improved preparedness and response to AMR.

A reliable and affordable energy supply is a fundamental prerequisite for reducing poverty, promoting investment, and boosting economic growth in the developing world. Among the different challenges that developing countries face, chronic energy crises are harrowing. The crises result from the unsatisfactory state of the central grid, a misguided energy mix, and ill-informed policies, among other things. The possibility of solving energy crises through a variety of alternative solutions is worth exploring. This review discusses two paths of energy development side by side: a traditional “hard” path of energy development (i.e., central grid extension powered by fossil fuels and nuclear energy expansion) and a relatively recent “soft” path of energy development, which is based on energy conservation and the deployment of renewable energy resources. This paper focuses on one central axis of the discussion: centralization vs. decentralization. This discussion, in turn, has technological, economic/business, and political dimensions. Finally, the paper discusses the significance of the debate from meeting the developing world’s energy demands. The paper intends not to prefer one or another path of energy development, nor it gives recommendations on diffusing or adopting those development paths. Instead, it explores the literature’s central arguments that might help frame the questions for further research. While this debate could be used to ask interesting questions that might help solve the energy crisis in the developing world, the discussion informs countries to advance policies specific to their circumstances under the umbrella of a sound and thoughtful energy productivity policy framework.

This research investigates the alignment of soft power and institutional skills in Montenegro's journey towards accession to the European Union (EU), with a particular focus on the environmental sector. An online survey targeting individuals employed in state institutions directly engaged in negotiation processes, notably the Ministry of Sustainable Development and Tourism and the Agency for Nature and Environmental Protection, was conducted. The research conducted an online survey, distributed before and after the summer recess to accommodate the transition of power following parliamentary elections, aimed at assessing the effectiveness of current personnel and identifying areas for improvement in staffing and negotiation strategies within Montenegro's environmental sector. Employing diverse methodologies, the survey's analysis delved into the demographic, social, and professional backgrounds of respondents. It explored their roles within institutions, involvement in environmental negotiations, and possession of relevant skills and expertise. Furthermore, respondents' knowledge of environmental issues, legislation, and challenges facing the country was assessed to gauge institutional capacity for environmental governance. Demographic data, including gender, age, education and regional origin, were collected to understand gender-specific attitudes and regional disparities in environmental perspectives. The sample of 84 individuals, comprising executives and employees from both institutions, provided insights into the age structure and regional diversity of personnel involved in negotiation tasks for Chapter 27. The selection of the Ministry of Sustainable Development and Tourism and the Agency for Nature and Environmental Protection reflects their pivotal roles in shaping Montenegro's environmental policies and addressing climate change challenges. This study aims to illuminate the dynamics of environmental governance within Montenegro's state administration, contributing to the country's path towards EU accession. The research findings highlight the critical need for Montenegro to prioritize strategic initiatives in personnel management, skill development, and institutional capacity-building within its environmental sector. The implications of this research extend beyond academia to inform policymaking and societal action, emphasizing the urgency for Montenegro to bolster its environmental sector capabilities, fostering both EU alignment and sustainable governance practices for the benefit of present and future generations.

The rehabilitation of the road embankments alongside the irrigation canal, which is constructed on a Bangkok soft clay foundation, has resulted from land use growth for several decades. As a result, the embankment is always confronted with the problem of instability. Numerous articles have demonstrated that rapid drawdown of the water level in the canal could be one of the most significant reasons, whereas vehicle cyclic loading may potentially contribute to some effect of the embankment failure. To explore and assess the effects of the influence factors, the finite element method (FEM) and conventional and dynamic triaxial approaches were employed. The study also investigated the consequences of varying thicknesses of soft clay and cyclic loading with different magnitudes and frequencies. Consequently, cyclic loading can lead to an augmentation in strain distribution and excess pore water pressure. Likewise, more significant deformation and excess pore water pressure were induced by a lower frequency and deeper thickness of soft clay compared to a higher frequency and thinner thickness. In brief, vehicle repetitive loading is one of the primary factors contributing to embankment failure, with the threshold stress being approximately three-fourths of the undrained shear strength. In contrast, threshold strain is approximately one to two-fold of the monotonic strain condition.

Chemical investigation of the Chinese soft coral Lobophytum sp. has resulted in the isolation of six new compounds, namely lobosteroids A–F (1–6), along with four known compounds. Their structures were determined by extensive spectroscopic analysis and comparison with the spectral data reported in the literature. Among them, the absolute configuration of 1 was determined by X-ray diffraction analysis. These steroids characterized by either the presence of an α,β-αꞌ,βꞌ-unsaturated carbonyl or an α,β-unsaturated carbonyl moiety in ring A, or the existence of a 5α,8α-epidioxy system in ring B, as well as diverse oxidation sites of side chains. The prelimi-nary antibacterial bioassay showed all compounds exhibited significant antibacterial activities against the fish pathogenic bacteria Streptococcus parauberis FP KSP28 and Phoyobacterium damselae FP2244 with all inhibition rates more than 90% at the concentration of 150 µM. And at the same concentration, compounds 2, 6–10 also displayed potent inhibitory effects against vancomy-cin-resistant Enterococcus faecium bacteria G7 with all inhibition rates more than 90%.

Pathological aseptic calcification is the most common form of structural valvular degeneration (SVD), leading to premature failure of heart valve bioprostheses (BHVs). The processing methods used to obtain GA-fixed pericardium-based biomaterials determine the hemodynamic characteristics and durability of BHVs. This article presents a comparative study of the effects of several processing methods on the degree of damage to the ECM of GA-fixed pericardium-based biomaterials as well as on their biostability, biocompatibility, and resistance to calcification. Based on the assumption that preservation of the native ECM structure will enable the creation of calcinosis-resistant materials, this study provides a soft biomimetic approach for the manufacture of GA-fixed biomaterials using gentle decellularization and washing methods. It has been shown that the use of soft methods for preimplantation processing of materials, ensuring maximum preservation of the intactness of the pericardial ECM, radically increases the resistance of biomaterials to calcification. The data obtained are of interest for the development of new calcinosis-resistant biomaterials for the manufacture of BHVs.

Refineries execute a series of interlinked processes, where the product of one unit serves as the input to another process. Potential failures within these processes affect the quality of the end products, operational efficiency, and revenue of the entire refinery. In this context, implementation of a real-time cognitive module, referring to predictive machine learning models, enables to provide equipment state monitoring services and to generate decision-making for equipment operations. In this paper, we propose two machine learning models: 1) to forecast the amount of pentane (C5) content in the final product mixture; 2) to identify if C5 content exceeds the specification thresholds for the final product quality. We validate our approach by using a use case from a real-world refinery. In addition, we develop a visualization to assess which features are considered most important during feature selection, and later by the machine learning models. Finally, we provide insights on the sensor values in the dataset, which help to identify the operational conditions for using such machine learning models.

The X-ray induced spin crossover transition of an Fe(II) molecular thin film in the presence and absence of a magnetic field has been investigated. The thermal activation energy barrier in the soft X-ray activation of the spin crossover transition for [Fe{H2B(pz)2}2(bipy)] molecular thin films is reduced in the presence of an applied magnetic field, as measured through X-ray absorption spectroscopy at various temperatures. The influence of a 1.8 T magnetic field is sufficient to cause deviations from the expected exponential spin state transition behavior that is measured in the field free case. We find that orbital moment diminishes with increasing temperature, relative to the spin moment in the vicinity of room temperature.

Drops are the most important and most common energy dissipator in irrigation networks and erodible canals and consequently, their performance must be well understood. This study was designed to evaluate the capability of Artificial Intelligence (AI) methods including ANN, ANFIS, GRNN, SVM, GP, MLR, and LR to predict the relative energy dissipation (∆E/E0) in vertical drops equipped with a horizontal screen. For this study, 108 experiments were carried out to investigate energy dissipation with variable discharge, varying drop height, and porosity of the horizontal screens. Parameters yc/h, yd/yc, and p are considered as input variables and ∆E/E0 is the output variable. The efficiency of models was compared using Taylor's diagram, Box Plot of the applied error distribution, correlation coefficient (CC), mean absolute error (MAE) and root-mean-square error (RMSE). Results indicate that the performance of the ANFIS_gbellmf based model with CC value of 0.9953, RMSE value of 0.0069 and MAE value of 0.0042 was superior to other applied models. Also, the linear regression model with CC=0.9933, RMSE=0.0083, and MAE= 0.0067performs better than the multiple linear regression model in this study. Results of a sensitivity study suggest that yc/h is the most effective parameter for predicting ∆E/E0.

Low back pain (LBP) is a common musculoskeletal complaint that can impede physical function and mobility. Current management often involves pain medication, but there is a need for non-pharmacological and non-invasive interventions. Soft tissue manipulation (STM) such as massage has been shown to be effective in human subjects, but the molecular mechanisms underlying these findings are not well understood. In this paper, we evaluated potential changes in soft tissue levels of more than thirty pro- or anti-inflammatory cytokines following instrument-assisted STM (IASTM) in rats with chronic, induced LBP using Complete Freund’s Adjuvant. Our results indicate that IASTM is associated with reduced soft tissue levels of RANTES/CCL5 and increased soft tissue levels of IL-4, which are pro-inflammatory and anti-inflammatory factors, respectively, by 120 minutes post-treatment. IASTM was not associated with tissue-level changes in CXCL5/LIX (the murine homologue of IL-8), CXCL7, GM-CSF ICAM-1, IL1-ra, IL-6, IP-10/CXCL10, L-selectin, TNF-α, or VEGF at either 30- or 120 minutes post-treatment. Combined, our findings suggest that IASTM exerts tissue-level effects that are associated with improved clinical outcomes and potentially beneficial changes in pro/anti-inflammatory cytokines in circulation and at the tissue level.

Objectives (Purpose) This study aims to evaluate the outcomes of the Subcrestally Placed Implant (SPI) technique in single molar cases, focusing on biological stability and aesthetics. It proposes a schematic model to elucidate the interplay between the biological stability of soft tissues and bone around the SPI and the morphological requisites that Implant Abutment Prostheses (IAP) must fulfill to effectively replace natural teeth. Materials and methods I examined 20 cases using the SPI technique with Internal Platform Switching (IPS) design implants for single molar replacements to assess their stability. Routine check-ups utilized plain panoramic X-rays to measure changes in crestal bone on the mesial and distal sides. Additionally, 10 cases with CBCT X-rays taken more than one year after the initial surgery underwent a novel 3-dimensional soft tissue analysis (3DSTA). Measurements included placement depths (PD), soft tissue thickness (STT) at central (cPD, cSTT) and peripheral areas (pPD, pSTT), the length of the Transitional Zone (TZ) on mesial, distal, facial, and lingual aspects, and crestal bone thickness (CBT) at buccal and lingual sites. Results Panoramic analyses showed minimal changes in crestal bone (mean changes of pPD were less than 0.1 mm) over an average period of 3.3 years. Average measurements were as follows: cPD was 1.7 mm, pPD was 2.7 mm, cSTT was 0.2 mm, pSTT was 0.6 mm, TZ length was 3.8 mm, buccal CBT was 3.0 mm, and lingual CBT was 3.7 mm. Conclusions CBCT analyses of the topographical relationships between soft tissue and crestal bone with IAP for SPIs demonstrated stable results over an average 3-year period. The consistency in the relationship between crestal bone and surrounding soft tissue can be ascribed to biological structural integrity. The study classified peri-implant soft tissues into subcrestal and supracrestal (transitional zone – TZ) segments, exploring their characteristics through dimensional measurements and assessing mechanical resistance. Further histological study is needed to identify specific features of each segment.

Due to the highly nonlinear, multi-stage, and strongly time-varying marine lysozyme fermentation process, it is difficult to assure the stability and prediction accuracy of the traditional single global soft sensor model on a global scale. This study innovatively proposed a soft sensor model based on an improved seagull optimization algorithm (ISOA) combined with Gaussian process regression (GPR) weighted ensemble learning. First, the sample data set is divided into multiple local sample subsets by the improved density peak clustering algorithm (ADPC). Second, the Gaussian process regression model is optimally altered with an improved seagull optimization algorithm for the purpose of establishing the corresponding sub-prediction model. Finally, the prediction model's fusion strategy is ultimately determined depending on the degree of connection between the test samples and a subset of local pieces. Simulation results show that the proposed soft sensor model, which searches GPR based on ISOA and combines various sub-models, can predict the key biochemical parameters of the marine lysozyme fermentation process better with less prediction error under the condition of fewer training data, and it can be expanded to the soft sensor models of general nonlinear systems, according to simulation results.

Several types of soft tissue sarcomas have peripheral infiltrative growth characteristics called tail-like lesions. The efficacy of neoadjuvant therapy for tumors with tail-like lesions has not been elucidated. From 2012 to 2019, we analyzed 36 patients with soft tissue sarcoma with tail-like lesions treated with neoadjuvant therapy, including chemotherapy, radiotherapy, or both. The ef-fect of neoadjuvant therapy on the tail sign was investigated by analyzing the change in tail-like lesions during neoadjuvant therapy and histological responses. The median length of the tail-like lesion reduced from 29.5 mm at initiation to 19.5 mm after neoadjuvant therapy. The extent of shrinkage in tail-like lesion was related to the histopathological responses in the main part. Com-plete disappearance of the tail-like lesion was observed in 12 patients; however, it was not related to achieving a microscopically negative margin. The oncologic outcomes did not significantly differ between cases with complete disappearance of tail-like lesions or not. This study indicated the shrinkage of tail-like lesions did not have significant effect on complete resection or improve-ment of clinical outcomes. A more comprehensive evaluation is needed to elaborate on the surgi-cal strategy.

Following the general aim of recapitulating the native mechanical properties of tissues and organs in vitro, the field of materials science and engineering has benefited from recent progress in developing compliant substrates with similar physical and chemical properties. In particular, in the field of mechanobiology, soft hydrogels can now reproduce the precise range of stiffnesses of healthy and pathological tissues to study the mechanisms behind cell response to mechanics. However, it was shown that biological tissues are not only elastic but also relax at different timescales. Cells can indeed perceive and actually need this dissipation because it is a critical signal integrated with other signals to define adhesion, spreading and even more complicated functions. The mechanical definition of hydrogels used in mechanobiology is however commonly limited to the elastic stiffness (Young’s modulus) and this value is known to depend greatly on the measurement conditions that are rarely reported. Here, we report that a simple relaxation test performed under well defined conditions can provide all the necessary information to characterize soft materials mechanically, by fitting the dissipation behavior with a generalized Maxwell model (GMM). The method was validated using soft polyacrylamide hydrogels and proved to be very useful to unveil precise mechanical properties of gels that cells can sense and offer a set of characteristic values that can be compared with what is typically reported from microindentation tests.

Magnetic properties of soft magnetic composites are highly sensitive to the processing conditions. In this paper we focus on the possibility to model this effect using the Jiles-Atherton-Sablik theory. It is assumed that the effect of varying compaction pressure may be described by direct introduction of stress-dependent term in the model equations. The values of model parameters are kept constant. Verification of the proposed approach is carried out using measurement data from self-developed iron-based composite cores.