Low-Cost Method for Waveguide Device Components Fabrication at 220 – 325 GHz

This work explores a rapid design and manufacturing approach to realize complex 3D pillar type filter and transmission line structures for applications in the 220 - 325 GHz range and which cannot be economically reproduced by conventional machining processes or present rapid prototyping methods. The significance of this investigation is that at sub-millimetre-wave or THz frequencies, where the waveguide features are less than 100μm and the skin depths are less than 200nm, the exact conductor shape and surface roughness have a significant electrical effect and any variations result in an important disagreement between the modelled and measured characteristics. This is a proof of concept validation of the rapid manufacturing approach and is aimed at paving the way to a range of THz passive waveguide components, where the availability and cost of such components is typically prohibitive and where the surface roughness is minimized and highly reproducible. Using this approach the fabrication times can be as rapid as a few days and can yield many hundreds of highly reproducible millimetre scale components

Quality management of cut carnation 'Tempo' with 1- MCP

Water relation and chlorophyll content are two important factors on the postharvest quality of cut flowers. 1-MCP (1–methylcyclopropene), as a gaseous inhibitor of ethylene action, significantly delayed the wilting ofcut carnation (Dianthus caryophyllus L.). The effects of 1-MCP depends on concentration, time duration and temperature. In this study, the effect of different 1-MCP concentrations (0, 20, 40, 60, 80 and 100 nl l-1) andtime durations (3, 6 and 9 h) on the vaselife, water uptake, loss of fresh weight and chlorophyll index of cut carnation 'Tempo' which is an ethylene-sensitive flower, were evaluated. The effects of 1-MCP concentrations and interaction between 1-MCP concentration and time duration on the vaselife, water uptake, loss of chlorophyll index and loss of fresh weight, were significant at 1% levels of probability. Also the effect of time duration on the loss of chlorophyll index and loss of fresh weight was significant at 5%and on the water uptake was significant at 1% of probability. Treatment with 60 nl l-1 1-MCP for 3 h with 16.47 days vaselife, 2.57 ml g-1 fresh weight, 2.41 ml g-1 water uptake and 2.667 loss of chlorophyll index wasbetter than other treatments

Assessing gully erosion susceptibility using topographic derived attributes, multi-criteria decision-making, and machine learning classifiers

Gully erosion is an erosive process that contributes considerably to the shape of the earth’s surface and is a major contributor to land degradation and soil loss. This study applied a methodology for mapping gully erosion susceptibility using only topographic related attributes derived from a medium-resolution digital elevation model (DEM) and a hybrid analytical hierarchy process (AHP) and the technique for an order of preference by similarity to ideal solutions (TOPSIS) and compare the results with naïve Bayes (NB) and support vector machine learning (SVM) algorithms. A transboundary sub-basin in an arid area of southern Iraq was selected as a case study. The performance of the developed models was compared using the receiver operating characteristic curve (ROC). Results showed that the areas under the ROC were 0.933, 0.936, and 0.955 for AHP-TOPSIS, NB, and SVM with radial basis function, respectively, which indicated that the performance of simply derived AHP-TOPSIS model is similar to sophisticated NB and SVM models. Findings indicated that a medium resolution DEM and AHP-TOPSIS are a promising tool for mapping of gully erosion susceptibility

Blind topological measurement-based quantum computation

Blind quantum computation is a novel secure quantum-computing protocol that enables Alice, who does not have sufficient quantum technology at her disposal, to delegate her quantum computation to Bob, who has a fully fledged quantum computer, in such a way that Bob cannot learn anything about Alice's input, output and algorithm. A recent proof-of-principle experiment demonstrating blind quantum computation in an optical system has raised new challenges regarding the scalability of blind quantum computation in realistic noisy conditions. Here we show that fault-tolerant blind quantum computation is possible in a topologically protected manner using the Raussendorf-Harrington-Goyal scheme. The error threshold of our scheme is 0.0043, which is comparable to that (0.0075) of non-blind topological quantum computation. As the error per gate of the order 0.001 was already achieved in some experimental systems, our result implies that secure cloud quantum computation is within reach.Comment: 17 pages, 5 figure

Modeling of groundwater potential using cloud computing platform: A case study from nineveh plain, Northern Iraq

Knowledge of the groundwater potential, especially in an arid region, can play a major role in planning the sustainable management of groundwater resources. In this study, nine machine learning (ML) algorithms—namely, Artificial Neural Network (ANN), Decision Jungle (DJ), Aver-aged Perceptron (AP), Bayes Point Machine (BPM), Decision Forest (DF), Locally-Deep Support Vector Machine (LD-SVM), Boosted Decision Tree (BDT), Logistic Regression (LG), and Support Vector Machine (SVM)—were run on the Microsoft Azure cloud computing platform to model the groundwater potential. We investigated the relationship between 512 operating boreholes with a specified specific capacity and 14 groundwater-influencing occurrence factors. The unconfined aquifer in the Nineveh plain, Mosul Governorate, northern Iraq, was used as a case study. The groundwater-influencing factors used included elevation, slope, curvature, topographic wetness index, stream power index, soil, land use/land cover (LULC), geology, drainage density, aquifer saturated thickness, aquifer hydraulic conductivity, aquifer specific yield, depth to groundwater, distance to faults, and fault density. Analysis of the contribution of these factors in groundwater potential using information gain ratio indicated that aquifer saturated thickness, rainfall, hydraulic conductivity, depth to groundwater, specific yield, and elevation were the most important factors (average merit > 0.1), followed by geology, fault density, drainage density, soil, LULC, and distance to faults (average merit < 0.1). The average merits for the remaining factors were zero, and thus, these factors were removed from the analysis. When the selected ML classifiers were used to esti-mate groundwater potential in the Azure cloud computing environment, the DJ and BDT models performed the best in terms of all statistical error measures used (accuracy, precision, recall, F-score, and area under the receiver operating characteristics curve), followed by DF and LD-SVM. The probability of groundwater potential from these algorithms was mapped and visualized into five groundwater potential zones: very low, low, moderate, high, and very high, which correspond to the northern (very low to low), southern (moderate), and middle (high to very high) portions of the study area. Using a cloud computing service provides an improved platform for quickly and cheaply running and testing different algorithms for predicting groundwater potential

Bromocriptine for Idiopathic Intracranial Hypertension: A Retrospective Multicenter Cohort Study

Mahmoud M Morsy,1,&ast; Ahmed Y Azzam,1,&ast; Mohammed Tarek Mirdad,2 Alsaleem Mohammed Abadi,3 Saif Aboud M Alqahtani,4 Hana J Abukhadijah,5 Osman Elamin,6 Mohamed D Morsy,7 David J Altschul8,9 1October 6 University Hospital, October 6 University, Giza, Egypt; 2College of Medicine, King Khalid University, Abha, Saudi Arabia; 3Family and Community Medicine Department, College of Medicine, King Khalid University, Abha, Saudi Arabia; 4Internal Medicine Department, College of Medicine, King Khalid University, Abha, Saudi Arabia; 5Medical Research Center, Hamad Medical Corporation, Doha, Qatar; 6Department of Jordan Hospital Neurosurgery, Amman, Jordan; 7Department of Clinical Physiology, College of Medicine, King Khalid University, Abha, Saudi Arabia; 8Montefiore-Einstein Cerebrovascular Research Lab, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA; 9Department of Neurological Surgery, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA&ast;These authors contributed equally to this workCorrespondence: David J Altschul, Department of Neurological Surgery, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, 10467, USA, Email [email protected]: Idiopathic Intracranial Hypertension (IIH) is a disorder characterized by elevated intracranial pressure without an identifiable cause, commonly affecting young obese women. Current treatment strategies, including weight loss, acetazolamide, and surgical interventions, have limitations due to side effects, adherence challenges, and potential complications. Bromocriptine, a dopamine D2 receptor agonist, has emerged as a potential novel therapy due to its metabolic effects. This study aims to evaluate the safety and efficacy of bromocriptine in IIH management through a retrospective cohort analysis.Methods: A retrospective analysis was conducted, focusing on patients with IIH. Propensity score matching was applied to balance baseline characteristics, including age, sex, race, and BMI, between the bromocriptine and control groups. Key outcome measures, papilledema, headache severity, refractory IIH status, and acetazolamide dose dependency, were assessed at multiple follow-up intervals.Results: The bromocriptine group demonstrated significant improvement in papilledema and headache severity over 24 months, with early effects observed at one month. There was a marked reduction in refractory IIH (30.66% lower incidence at 24 months, p< 0.0001) and reduced dependency on acetazolamide from three months onward (p=0.0246). The safety profile was favorable, with comparable adverse event rates to controls, although allergic skin reactions were noted in the bromocriptine group.Conclusion: Bromocriptine shows promise as an effective and safe therapeutic option for IIH, with sustained improvement in clinical parameters and reduced reliance on conventional treatment. Future randomized controlled trials are needed to confirm these findings and explore optimal dosing strategies.Keywords: idiopathic intracranial hypertension, pseudotumor cerebri, intracranial pressure, bromocriptine, dopamin

Size-Tailored Physicochemical Properties of Monodisperse Polystyrene Nanoparticles and the Nanocomposites Made Thereof

The latex monodisperse polystyrene (PS) colloids are important for different advanced applications (e.g. in coating, biotechnology etc.). However, the size dependency of their structural properties that impacts the characteristics of the nanocomposites composed thereof is largely unknown. Here, monodisperse PS nanoparticles (MPNPs) are synthesized via emulsion polymerization in five sizes (50, 150, 300, 350, and 450 nm). The size of the PS MPNPs is tailored by controlling the reaction time, temperature, and amount of surfactant and initiator. The correlation between the particle size and structural properties of the PS MPNPs is established by different thermomechanical and optical characterizations. The smaller particles (50 and 150 nm) show a lower glass transition (Tg) and thermal decomposition temperature and a lower Raman peak intensity. Yet, they trigger a higher IR absorption, thanks to a larger surface area. When incorporated in a polyvinyl alcohol (PVA) matrix, the smaller particles impart the resulting nanocomposite a higher tensile strength, and elastic and storage moduli. Whereas, they decline the elongation and loss factor. The very few examples of the MPNPs incorporated polymeric nanocomposites have been unstudied from this perspective. Thus, these tangible knowledge can profit scalable production of this kind of nanocomposite materials for different applications in a cost/energy efficient manner.Peer reviewe

Socially and biologically inspired computing for self-organizing communications networks

The design and development of future communications networks call for a careful examination of biological and social systems. New technological developments like self-driving cars, wireless sensor networks, drones swarm, Internet of Things, Big Data, and Blockchain are promoting an integration process that will bring together all those technologies in a large-scale heterogeneous network. Most of the challenges related to these new developments cannot be faced using traditional approaches, and require to explore novel paradigms for building computational mechanisms that allow us to deal with the emergent complexity of these new applications. In this article, we show that it is possible to use biologically and socially inspired computing for designing and implementing self-organizing communication systems. We argue that an abstract analysis of biological and social phenomena can be made to develop computational models that provide a suitable conceptual framework for building new networking technologies: biologically inspired computing for achieving efficient and scalable networking under uncertain environments; socially inspired computing for increasing the capacity of a system for solving problems through collective actions. We aim to enhance the state-of-the-art of these approaches and encourage other researchers to use these models in their future work

An initial comparative map of copy number variations in the goat (Capra hircus) genome

<p>Abstract</p> <p>Background</p> <p>The goat (<it>Capra hircus</it>) represents one of the most important farm animal species. It is reared in all continents with an estimated world population of about 800 million of animals. Despite its importance, studies on the goat genome are still in their infancy compared to those in other farm animal species. Comparative mapping between cattle and goat showed only a few rearrangements in agreement with the similarity of chromosome banding. We carried out a cross species cattle-goat array comparative genome hybridization (aCGH) experiment in order to identify copy number variations (CNVs) in the goat genome analysing animals of different breeds (Saanen, Camosciata delle Alpi, Girgentana, and Murciano-Granadina) using a tiling oligonucleotide array with ~385,000 probes designed on the bovine genome.</p> <p>Results</p> <p>We identified a total of 161 CNVs (an average of 17.9 CNVs per goat), with the largest number in the Saanen breed and the lowest in the Camosciata delle Alpi goat. By aggregating overlapping CNVs identified in different animals we determined CNV regions (CNVRs): on the whole, we identified 127 CNVRs covering about 11.47 Mb of the virtual goat genome referred to the bovine genome (0.435% of the latter genome). These 127 CNVRs included 86 loss and 41 gain and ranged from about 24 kb to about 1.07 Mb with a mean and median equal to 90,292 bp and 49,530 bp, respectively. To evaluate whether the identified goat CNVRs overlap with those reported in the cattle genome, we compared our results with those obtained in four independent cattle experiments. Overlapping between goat and cattle CNVRs was highly significant (P < 0.0001) suggesting that several chromosome regions might contain recurrent interspecies CNVRs. Genes with environmental functions were over-represented in goat CNVRs as reported in other mammals.</p> <p>Conclusions</p> <p>We describe a first map of goat CNVRs. This provides information on a comparative basis with the cattle genome by identifying putative recurrent interspecies CNVs between these two ruminant species. Several goat CNVs affect genes with important biological functions. Further studies are needed to evaluate the functional relevance of these CNVs and their effects on behavior, production, and disease resistance traits in goats.</p