Super-Suppression of Long-Wavelength Phonons in Constricted Nanoporous Geometries.

In a typical semiconductor material, the majority of the heat is carried by long-wavelength, long-mean-free-path phonons. Nanostructuring strategies to reduce thermal conductivity, a promising direction in the field of thermoelectrics, place scattering centers of size and spatial separation comparable to the mean free paths of the dominant phonons to selectively scatter them. The resultant thermal conductivity is in most cases well predicted using Matthiessen's rule. In general, however, long-wavelength phonons are not as effectively scattered as the rest of the phonon spectrum. In this work, using large-scale molecular-dynamics simulations, non-equilibrium Green's function simulations, and Monte Carlo simulations, we show that specific nanoporous geometries that create narrow constrictions in the passage of phonons lead to anticorrelated heat currents in the phonon spectrum. This effect results in super-suppression of long-wavelength phonons due to heat trapping and reductions in the thermal conductivity to values well below those predicted by Matthiessen's rule.

On the role of surface morphology in impacting-freezing dynamics of supercooled droplets.

A thorough understanding of droplet impact and freezing is vital in preventing ice accretion on many outdoor devices. This simulation-based study investigated the effect of surface morphology on the impacting-freezing process of a supercooled droplet. Also, the variations of Weber number and supercooling temperature were studied numerically. The droplet impact and freezing process were simulated with the volume of fluid method and freezing model. A more accurate simulation was achieved by modeling the supercooled droplet and the dynamic contact angle. At the given ranges of the input parameters, the main factors that guaranteed droplet rebounding after collision were determined. The supercooling temperature and the groove width should be above 266 K and less than 0.21 mm, respectively. The droplet should also maintain its cohesion and integrity during impact. Creating grooves on a surface is novel and paves a new way to understand the impact and solidification of water droplets in supercooled conditions.

Reliable smart models for estimating frictional pressure drop in two-phase condensation through smooth channels of varying sizes.

Reliable and comprehensive predictive tools for the frictional pressure drop (FPD) are of particular importance for systems involving two-phase flow condensation. However, the available models are only applicable to specific operating conditions and channel sizes. Thus, this study aims at developing universal models to estimate the FPD during condensation inside smooth mini/micro and conventional (macro) channels. An extensive databank, comprising 8037 experimental samples and 23 working fluids from 50 reliable sources, was prepared to achieve this target. A comprehensive investigation on the literature models reflected the fact that all of them are associated with high deviations, and their average absolute relative errors (AAREs) exceed 26%. Hence, after identifying the most effective input variables through the Spearman's correlation analysis, three soft-computing paradigms, i.e., multilayer perceptron (MLP), gaussian process regression (GPR) and radial basis function (RBF) were employed to establish intelligent and dimensionless predictive tools for the FPD based on the separated model suggested by Lockhart and Martinelli. Among them, the most accurate results were presented by the GPR approach with AARE and R 2 values of 4.10%, 99.23% respectively, in the testing step. The truthfulness and applicability of the models were explored through an array of statistical and visual analyses, and the results affirmed the obvious superiority of the newly proposed approaches over the literature correlations. Furthermore, the novel predictive tools excellently described the physical variations of the condensation FPD versus the operating parameters. Ultimately, the order of importance of factors in controlling the condensation FPD was clarified by a sensitivity analysis.

Multidimensional signal detection modeling reveals Gestalt-like perceptual integration of face emotion and identity.

Numerous studies have tested the hypothesis that facial identity and emotional expression are independently processed, but a solid conclusion has been difficult to reach, with the literature showing contradictory results. We argue that this is partly due to different researchers using different definitions of perceptual integration and independence, usually vague and/or simply operational, and also due to lack of proper stimulus control. Here, we performed a study using three-dimensional realistic computer-generated faces for which the discriminability of identities and expressions, the intensity of the expressions, and low-level features of the faces were controlled. A large number of participants, distributed across twelve experimental groups, performed identification tasks for the six basic emotional expressions and the neutral expression (between 2018 and 2019). A multidimensional signal detection model was utilized to analyze the data, which allowed us to dissociate between multiple formally defined notions of independence and holism. Results showed strong and robust violations of perceptual independence that were consistent across all experiments and suggest Gestalt-like perceptual integration of face identity and expression. To date, our results provide the strongest evidence for holistic/Gestalt processing found among face perception studies that have used formal definitions of independence and holism. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Designing a community-supported agriculture model for increasing food security.

The institutionalization of participation is a topic that has been discussed in different ways over the last few decades. There are many diverse aspects of the agricultural sector and rural communities that can be identified and used to bring about a major change in agriculture. Community supported agriculture (CSA) is one of the participatory and sustainable approaches that can be used in this regard. CSA is a relatively new socioeconomic model for producing food materials, increasing food security, improving the quality of food materials and conserving agricultural land, plants and animals. This research aimed to design a CSA model that was operationalized in Markazi province, Iran, with the aim of increasing food security. It was a survey study applied through a questionnaire. The statistical population (N=110) consisted of all active farmers in Ghazel Dareh village who were selected through the census method. The necessary information was collected through a questionnaire (84 of which were completed and returned) and analyzed using SPSS v. 25 and LISREL. The results showed that economic, socio-institutional, policy-making, educational and infrastructural factors significantly influenced the development of CSA. Infrastructural and socio-institutional factors with impact factors of 0.88 and 0.54 had the largest and smallest effect on CSA, respectively. Finally, since all impact factors were positive, we can say that improving each of these factors could improve the development of CSA in the study area.

Study of waterpipe smoking topography in Fars province of Iran.

Despite a sharp increase in the use of the waterpipe (WP) has been noted recently in Iran, no information is available for the smoking behavior and topography parameters. The present study is intended to obtain the inhalation and smoking topography parameters for the Iranian WP smokers. The smoking data collected from 122 smoking sessions, including 192 WP smokers in the Iranian Fars province have been used to perform smoking topography assessments. The influence of demographic and smoking parameters on puffing data is obtained. Results have indicated that gender and tobacco type strongly affect puff volume and duration. Women smokers inhale smaller volume of smoke than men and puff duration is significantly increased for regular smokers than occasional smokers. However, the results of the present study have not revealed a major effect of age, residence and setting on the puffing behavior.

Comparing infusion-related reactions of the first full dose (600 mg) biosimilar ocrelizumab administration with the standard divided protocol in multiple sclerosis patients: a randomized controlled trial study.

BACKGROUND: Ocrelizumab is a humanized antiCD20, thought to be a highly effective disease-modifying therapy (DMT). Its most frequent adverse effects are infusion-related reactions (IRRs). To reduce these reactions, the first dose of ocrelizumab is administered as two 300 mg infusions separated by two weeks. However, in the phase II trial of ocrelizumab, severe IRRs were not significantly different between two doses of 600 mg dose (two separate 300 mg doses) and 2000 mg dose (two separate 1000 mg doses). We compared the IRRs in undivided full (one 600 mg) and divided (two 300 mg) doses of ocrelizumab which is the standard protocol. METHODS: MS patients (relapsing or primary progressive MS) who are selected to receive ocrelizumab by neurologist or MS fellowship were enrolled in an open-label randomized controlled trial. Iranian biosimilar of the drug (Xacrel® by Cinnagen, approved by the Iranian Food and Drug Administration in 2021) was used. The participants received the first dose of ocrelizumab as either one 600 mg dose in one session or two 300 mg doses in two weeks apart. IRRs during or in the first 24 h after infusion were recorded. RESULTS: Of 332 participants, 150 received two 300 mg doses, and 182 received one 600 mg dose (by random selection). Life-threatening adverse effects were not observed in both groups. Overnight admission or permanent drug discontinuation was not needed. Temporary drug discontinuation was significantly higher in the one 600 mg dose group (p-value < 0.001). During the infusions, malaise (p-value: 0.003), skin reactions (p-value: 0.04), throat swelling (p-value: 0.03), and dyspnea (p-value: 0.01) were significantly increased in the intervention group. However, in the first 24 h, there was no significant difference between two different treatment protocols (one 600 mg dose or two 300 mg doses) in the onset of IRRS (p-value: 0.12). CONCLUSION: These findings suggest one 600 mg dose of ocrelizumab administration for the first dose is relatively safe. With some protocol modifications, it could lead to fewer patient referrals, saving time and cost and improvement the access for patients.

Toward Personalized Cognitive Training in Older Adults: A Pilot Investigation of the Effects of Baseline Performance and Age on Cognitive Training Outcomes.

BACKGROUND: Cognitive training holds potential as a non-pharmacological intervention to decrease cognitive symptoms associated with Alzheimer's disease (AD), but more research is needed to understand individual differences that may predict maximal training benefits. OBJECTIVE: We conducted a pilot study using a six-month training regimen in healthy aging adults with no cognitive decline. We investigated the effects of baseline performance and age on training and transfer improvements. METHODS: Out of 43 participants aged 65-84 years, 31 successfully completed cognitive training (BrainHQ) in one of three cognitive domains: processing speed (N = 13), inhibitory control (N = 9), or episodic memory (N = 9). We used standardized assessments to measure baseline performance and transfer effects. RESULTS: All 31 participants improved on the cognitive training regimen and age was positively associated with training improvement (p = 0.039). The processing speed group improved significantly across many near- and far-transfer tasks. In the inhibitory control group, individuals with lower baseline performance improved more on inhibitory control and cognitive flexibility tasks. In the episodic memory group, older individuals improved most on a memory task while younger individuals improved most on an executive function far-transfer task. CONCLUSIONS: Individual differences are predictive of cognitive training gains, and the impact of individual differences on training improvements is specific to the domain of training. We provide initial insight regarding how non-pharmacological interventions can be optimized to combat the onset of cognitive decline in older adults. With future research this work can inform the design of effective cognitive interventions for delaying cognitive decline in preclinical AD.

A fully-flexible and thermally adjustable implantable neural probe with a U-turn polyester microchannel.

This work presents a fully flexible implantable neural probe fabricated with Polydimethylsiloxane (PDMS) and including a thermally-tunable stiffness microchannel filled with Polyester. The probe includes an optimized microfluidics mixer for drug delivery. Polyester, which is solid at room temperature and has a low melting point close to body temperature, is used to decrease the stiffness of the probe after insertion, after getting in contact with tissues. We designed a U-turn microchannel inside the PDMS neural probe and filled it up with melted polyester. The microchannel has a cross-section of 30 µm × 5 µm and a length of 14.7 mm. The following probe dimensions were chosen after extensive simulation: thickness = 20 µm, width = 300 µm, and length = 7 mm. These values yield a buckling force above 1 mN, which is sufficient for proper insertion into the brain tissues. Simulation results show that the microfluidics mixer with a cross-section of 90 µm × 5 µm and a length of 7 mm has optimum performance for the desired flow rate and quantity of drug to deliver. The pressure drop inside the microfluidic channel is less than 0.43 kPa, which is appropriate for PDMS-PDMS bonding, whereas the Reynolds number is near 1.91k in the laminar regime. No leakage or bubble occurred during the experimental validation, which suggests an appropriate pressure and a laminar flow in the channel.

Class-imbalanced Unsupervised and Semi-Supervised Domain Adaptation for Histopathology Images.

In dealing with the lack of sufficient annotated data and in contrast to supervised learning, unsupervised, self-supervised, and semi-supervised domain adaptation methods are promising approaches, enabling us to transfer knowledge from rich labeled source domains to different (but related) unlabeled target domains, reducing distribution discrepancy between the source and target domains. However, most existing domain adaptation methods do not consider the imbalanced nature of the real-world data, affecting their performance in practice. We propose to overcome this limitation by proposing a novel domain adaptation approach that includes two modifications to the existing models. Firstly, we leverage the focal loss function in response to class-imbalanced labeled data in the source domain. Secondly, we introduce a novel co-training approach to involve pseudo-labeled target data points in the training process. Experiments show that the proposed model can be effective in transferring knowledge from source to target domain. As an example, we use the classification of prostate cancer images into low-cancerous and high-cancerous regions.

Comparison of Three Different Methods of Transfection for the Production of Recombinant Adenovirus Expressing Human Carcinoembryonic Antigen Gene.

Adenoviral vectors (AdVs) are widely used as a gene delivery vehicle and vaccine design due to their genetic stability, transfer capacity of large genes, production at high titers, and remarkable efficacy of transduction. One of the most important applications of AdVs is in cancer immunotherapy. Tumor-associated antigens are overexpressed in cancer cells; however, they cannot induce immune responses sufficiently. Therefore, the immune system must be stimulated against these antigens to kill the cancer cells. This study described the construction steps of a recombinant AdV expressing human carcinoembryonic antigen (CEA) gene. Furthermore, in order to achieve a high titer of the virus, an efficient transfection was required. Three various transfection reagents were compared to achieve the best method of transfection. Carcinoembryonic antigen was cloned into the pAdV and transfected into the A293 cells using three different reagents, including polyethylenimine (PEI), calcium phosphate, and DMRIE-C. The PEI had the highest transfection efficiency, which was selected for the transfection of the recombinant plasmid. It has low toxicity for cells and is suitable for large-scale transfection. The virus produced in this study can be applied as a vaccine in cancer immunotherapy for stimulating the immune system against CEA-expressing tumors.

The role of skill development in improving the performance of agricultural extension agents in Iran using structural equation modeling and grounded theory.

Performance improvement is the main concept of development policy. Belief in strengthening and improving the performance of individuals and institutions in developing countries for success in development policy has gradually formed among development agents. Performance improvement at the individual level pays attention to individual needs in order to enhance performance. Development requires developed and trained people. Therefore, the better the human resources as wealth and national capital are cultivated, the smoother the development path will be. The dimensions of improving performance at the individual level include things such as abilities, needs, attitudes, psychology, motivations, talents and skills, which also raises the need for skill development. In this regard, the current research seeks to investigate the relationship between skill development and performance improvement in extension in Iranian agriculture. The statistical population includes agricultural jihad centers in five regions of the country (the division of the country's provinces according to the Ministry of Agricultural Jihad, where each region includes 6 provinces) which is 8142 people, and accordingly, Cochran's formula was used to determine the sample size and the number of sample size 366 people were obtained. A structured questionnaire was developed to collect data. Structural equation modeling was used to examine the skill development measurement model, the performance improvement measurement model, and the skill development model. The research results show the significant relationship of all the indicators extracted from the interview in the structural equations.

Early occurrence of acute myelomonocytic leukemia (M4/M5) after liver transplantation: a case report.

INTRODUCTION: Acute myeloid leukemia is a rare event in post-liver-transplantation recipients. In the present report, we described a case of extramedullary acute myeloid leukemia, M4/M5 subtype, following orthotopic liver transplant. CASE PRESENTATION: The patient was a 50-year-old Iranian woman who underwent orthotopic liver transplant due to hepatitis B-related cirrhosis (Child C, MELD (model for end-stage liver disease score) = 22). Orthotopic liver transplant was performed using the piggy back technique in January 2022. Induction immunosuppressive therapy was 1 gm methylprednisolone for 3 days followed by a triple maintenance immunosuppressive regimen including mycophenolate mofetil, prednisolone, and tacrolimus. About 5 months after orthotopic liver transplant in June 2022, the patient presented with leukocytosis, with white blood cell count of 99.4 × 103/µl, and physical examination revealed only cervical lymphadenopathy. Biopsy of cervical lymph nodes showed a myeloid tumor. She was immediately hospitalized. Eight hours after hospitalization, the patient gradually developed lethargy and decreased O2 saturation to approximately 89%. Flow cytometry demonstrated the markers of a myelomonocytic acute myeloid leukemia (M4/M5). Cytoreduction was immediately started by intensive leukopheresis followed by induction therapy. Because of a septic complication during the induction therapy, further chemotherapy was discontinued and broad-spectrum antibiotics and antifungal treatments started. Unfortunately, our patient died of severe septic shock 42 days after hospitalization. CONCLUSION: Acute myeloid leukemia is a rare phenomenon after liver transplantation, and it can follow a rapidly fatal clinical course.

Entropic equilibrium for the lattice Boltzmann method: Hydrodynamics and numerical properties.

The entropic lattice Boltzmann framework proposed the construction of the equilibrium by taking into consideration minimization of a discrete entropy functional. The effect of this entropic equilibrium on properties of the resulting solver has been the topic of discussions in the literature. Here we present a rigorous analysis of the hydrodynamics and numerics of the entropic equilibrium. We demonstrate that the entropic equilibrium features unconditional linear stability, in contrast to the conventional polynomial equilibrium. We reveal the mechanisms through which unconditional linear stability is maintained, most notable of which are adaptive propagation velocity of normal modes and the positive-definite nature of the dissipation rates of hydrodynamic eigenmodes. We further present a simple local correction to considerably reduce the deviations in the effective bulk viscosity.

Proportionally Fair Hospital Collaborations in Federated Learning of Histopathology Images.

Medical centers and healthcare providers have concerns and hence restrictions around sharing data with external collaborators. Federated learning, as a privacy-preserving method, involves learning a site-independent model without having direct access to patient-sensitive data in a distributed collaborative fashion. The federated approach relies on decentralized data distribution from various hospitals and clinics. The collaboratively learned global model is supposed to have acceptable performance for the individual sites. However, existing methods focus on minimizing the average of the aggregated loss functions, leading to a biased model that performs perfectly for some hospitals while exhibiting undesirable performance for other sites. In this paper, we improve model "fairness" among participating hospitals by proposing a novel federated learning scheme called Proportionally Fair Federated Learning, short Prop-FFL. Prop-FFL is based on a novel optimization objective function to decrease the performance variations among participating hospitals. This function encourages a fair model, providing us with more uniform performance across participating hospitals. We validate the proposed Prop-FFL on two histopathology datasets as well as two general datasets to shed light on its inherent capabilities. The experimental results suggest promising performance in terms of learning speed, accuracy, and fairness.

Intelligent modeling of hydrogen sulfide solubility in various types of single and multicomponent solvents.

This study aims to study the solubility of acid gas, i.e., hydrogen sulfide (H2S) in different solvents. Three intelligent approaches, including Multilayer Perceptron (MLP), Gaussian Process Regression (GPR) and Radial Basis Function (RBF) were used to construct reliable models based on an extensive databank comprising 5148 measured samples from 54 published sources. The analyzed data cover 95 single and multicomponent solvents such as amines, ionic liquids, electrolytes, organics, etc., in broad pressure and temperature ranges. The proposed models require just three simple input variables, i.e., pressure, temperature and the equivalent molecular weight of solvent to determine the solubility. A competitive examination of the novel models implied that the GPR-based one gives the most appropriate estimations with excellent AARE, R2 and RRMSE values of 4.73%, 99.75% and 4.83%, respectively for the tested data. The mentioned intelligent model also performed well in describing the physical behaviors of H2S solubility at various operating conditions. Furthermore, analyzing the William's plot for the GPR-based model affirmed the high reliability of the analyzed databank, as the outlying data points comprise just 2.04% of entire data. In contrast to the literature models, the newly presented approaches proved to be applicable for different types of single and multicomponent H2S absorbers with AAREs less than 7%. Eventually, a sensitivity analysis based on the GPR model reflected the fact that the solvent equivalent molecular weight is the most influential factor in controlling H2S solubility.

Decoding the heterogeneity of Alzheimer's disease diagnosis and progression using multilayer networks.

Alzheimer's disease (AD) is a multifactorial and heterogeneous disorder, which makes early detection a challenge. Studies have attempted to combine biomarkers to improve AD detection and predict progression. However, most of the existing work reports results in parallel or compares normalized findings but does not analyze data simultaneously. We tested a multi-dimensional network framework, applied to 490 subjects (cognitively normal [CN] = 147; mild cognitive impairment [MCI] = 287; AD = 56) from ADNI, to create a single model capable of capturing the heterogeneity and progression of AD. First, we constructed subject similarity networks for structural magnetic resonance imaging, amyloid-ß positron emission tomography, cerebrospinal fluid, cognition, and genetics data and then applied multilayer community detection to find groups with shared similarities across modalities. Individuals were also followed-up longitudinally, with AD subjects having, on average, 4.5 years of follow-up. Our findings show that multilayer community detection allows for accurate identification of present and future AD (≈90%) and is also able to identify cases that were misdiagnosed clinically. From all MCI participants who developed AD or reverted to CN, the multilayer model correctly identified 90.8% and 88.5% of cases respectively. We observed similar subtypes across the full sample and when examining multimodal data from subjects with no AD pathology (i.e., amyloid negative). Finally, these results were also validated using an independent testing set. In summary, the multilayer framework is successful in detecting AD and provides unique insight into the heterogeneity of the disease by identifying subtypes that share similar multidisciplinary profiles of neurological, cognitive, pathological, and genetics information.