Clinical and genetic investigation of 14 families with various forms of short stature syndromes.

Skeletal dysplasias are a heterogeneous group of disorders presenting mild to lethal defects. Several factors, such as genetic, prenatal, and postnatal environmental may contribute to reduced growth. Fourteen families of Pakistani origin, presenting the syndromic form of short stature either in the autosomal recessive or autosomal dominant manner were clinically and genetically investigated to uncover the underlying genetic etiology. Homozygosity mapping, whole exome sequencing, and Sanger sequencing were used to search for the disease-causing gene variants. In total, we have identified 13 sequence variants in 10 different genes. The variants in the HSPG2 and XRCC4 genes were not reported previously in the Pakistani population. This study will expand the mutation spectrum of the identified genes and will help in improved diagnosis of the syndromic form of short stature in the local population.

Wide range and highly linear signal processed systematic humidity sensor array using Methylene Blue and Graphene composite.

This paper proposes a signal processed systematic 3 × 3 humidity sensor array with all range and highly linear humidity response based on different particles size composite inks and different interspaces of interdigital electrodes (IDEs). The fabricated sensors are patterned through a commercial inkjet printer and the composite of Methylene Blue and Graphene with three different particle sizes of bulk Graphene Flakes (BGF), Graphene Flakes (GF), and Graphene Quantum Dots (GQD), which are employed as an active layer using spin coating technique on three types of IDEs with different interspaces of 300, 200, and 100 µm. All range linear function (0-100% RH) is achieved by applying the linear combination method of nine sensors in the signal processing field, where weights for linear combination are required, which are estimated by the least square solution. The humidity sensing array shows a fast response time (Tres) of 0.2 s and recovery time (Trec) of 0.4 s. From the results, the proposed humidity sensor array opens a new gateway for a wide range of humidity sensing applications with a linear function.

Cereal processing waste, an environmental impact and value addition perspectives: A comprehensive treatise.

This review is to describe various methods used for the treatment of cereal processing wastes and their efficiency to reduce environmental issues. Physico-chemical and biological methods have great potential for the treatment of cereal industrial waste. These methods can be used alone or in combination with effective treatment. Physico-chemical treatments are mostly employed for the pretreatment of cereal processing wastes that helps in reduced sludge formation during biological treatments. Biological treatments are mostly used owing to their high efficiency in removing pollutants, and less expensive than physico-chemical treatments. However, these treatments consume more time as compared to physico-chemical treatments. These treatments also proved to be efficient for a high rate of cereal waste conversion into value-added products. Thus, cereal industrial waste can result in value-added products such as biohydrogen, bioethanol, butanol, biogas and biocoal as biofuels, industrial valued enzymes, biomass, biofertilizer, proteins, organic acids, polysaccharides and few others.

Inkjet printed self-healable strain sensor based on graphene and magnetic iron oxide nano-composite on engineered polyurethane substrate.

In recent years, self-healing property has getting tremendous attention in the future wearable electronic. This paper proposes a novel cut-able and highly stretchable strain sensor utilizing a self-healing function from magnetic force of magnetic iron oxide and graphene nano-composite on an engineered self-healable polyurethane substrate through commercialized inkjet printer DMP-3000. Inducing the magnetic property, magnetic iron oxide is applied to connect between graphene flacks in the nano-composite. To find the best nano-composite, the optimum graphene and magnetic iron oxide blending ratio is 1:1. The proposed sensor shows a high mechanical fracture recovery, sensitivity towards strain, and excellent self-healing property. The proposed devices maintain their performance over 10,000 times bending/relaxing cycles, and 94% of their function are recovered even after cutting them. The device also demonstrates stretchability up to 54.5% and a stretching factor is decreased down to 32.5% after cutting them. The gauge factor of the device is 271.4 at 35%, which means its sensitivity is good. Hence, these results may open a new opportunity towards the design and fabrication of future self-healing wearable strain sensors and their applied electronic devices.

The coexistence of threshold and memory switching characteristics of ALD HfO2 memristor synaptic arrays for energy-efficient neuromorphic computing.

The development of bioinspired electronic devices that can mimic the biological synapses is an essential step towards the development of efficient neuromorphic systems to simulate the functions of the human brain. Among various materials that can be utilized to attain electronic synapses, the existing semiconductor industry-compatible conventional materials are more favorable due to their low cost, easy fabrication and reliable switching properties. In this work, atomic layer deposited HfO2-based memristor synaptic arrays are fabricated. The coexistence of threshold switching (TS) and memory switching (MS) behaviors is obtained by modulating the device current. The TS characteristics are exploited to emulate essential synaptic functions. The Ag diffusive dynamics of our electronic synapses, analogous to the Ca2+ dynamics in biological synapses, is utilized to emulate synaptic functions. Electronic synapses successfully emulate paired-pulse facilitation (PPF), post-tetanic potentiation (PTP), spike-timing-dependent plasticity (STDP), short-term potentiation (STP), long-term potentiation (LTP) and transition from STP to LTP with rehearsals. The psychological memorization model of short-term memory (STM) to long-term memory (LTM) transition is mimicked by image memorization in crossbar array devices. Reliable and repeatable bipolar MS behaviors with a low operating voltage are obtained by a higher compliance current for energy-efficient nonvolatile memory applications.

Highly Sensitive and Full Range Detectable Humidity Sensor using PEDOT:PSS, Methyl Red and Graphene Oxide Materials.

Single transducer with humidity sensing materials has limitations in both range and sensitivity, which cannot be used to detect the full range of humidity with consistent sensitivity. To enlarge range and improve sensitivity in the all range relative humidity (RH), we propose a highly sensitive and full range detectable humidity sensor based on multiple inter-digital transducer (IDT) electrodes connected in series with poly(3,4-ethylenedioxythiophene) doped poly (styrene sulfonate) anions (PEDOT: PSS), C15H15N3O2 (Methyl Red), and graphene oxide (GO) thin films as the active sensing materials. The humidity sensor with single active material has a limit in the detecting ranges, where the GO, PEDOT: PSS, and Methyl Red materials have sensing responses of 0 to 78% RH, 30 to 75% RH, and 25 to 100% RH, respectively. However, a humidity sensor using combined three active materials can respond to much wider range of RH with high sensitivity, where the IDTs and the active regions were prepared using ink-jet printing and spin coating, respectively. This proposed sensor can detect a full range of 0% RH to 100% RH. The response and recovery times are 1 sec and 3.5 sec, respectively. Our single sensing device using multiple IDTs connected different active materials in series can overcome the limitations of single transducer based sensor for the high performance sensor applications.

Bio-compatible organic humidity sensor based on natural inner egg shell membrane with multilayer crosslinked fiber structure.

In this paper, we propose a novel bio-compatible organic humidity sensor based on natural inner egg shell membrane (IESM) with multilayer cross linked fiber structure that can be used as a substrate as well as a sensing active layer. To fabricate the proposed sensors, two different size inter digital electrodes (IDEs) with 10 mm × 4 mm for sensor 1 and 12 mm × 6 mm for sensor 2 are printed on the surface of the IESM through Fujifilm Dimatix DMP 3000 inkjet material printing setup, which have finger width of 100 µm and space of 100 µm. The fabricated sensors stably operates in a relative humidity (RH) range between 0% RH to 90% RH, and its output impedance and capacitance response are recorded at 1 kHz and 10 kHz. The response time (Tres) and recovery time (Trec) of sensor 1 are detected as ~1.99 sec and ~8.76 sec, respectively and the Tres and Trec of sensor 2 are recorded as ~2.32 sec and ~9.21 sec, respectively. As the IESM for the humidity sensor, the natural materials can be implemented in our daily life as they open a new gate way for bio-compatible devices.

Disposable all-printed electronic biosensor for instantaneous detection and classification of pathogens.

A novel disposable all-printed electronic biosensor is proposed for a fast detection and classification of bacteria. This biosensor is applied to classify three types of popular pathogens: Salmonella typhimurium, and the Escherichia coli strains JM109 and DH5-α. The proposed sensor consists of inter-digital silver electrodes fabricated through an inkjet material printer and silver nanowires uniformly decorated on the electrodes through the electrohydrodynamic technique on a polyamide based polyethylene terephthalate substrate. The best sensitivity of the proposed sensor is achieved at 200 µm teeth spaces of the inter-digital electrodes along the density of the silver nanowires at 30 × 103/mm2. The biosensor operates on ±2.5 V and gives the impedance value against each bacteria type in 8 min after sample injection. The sample data are measured through an impedance analyzer and analyzed through pattern recognition methods such as linear discriminate analysis, maximum likelihood, and back propagation artificial neural network to classify each type of bacteria. A perfect classification and cross-validation is achieved by using the unique fingerprints extracted from the proposed biosensor through all the applied classifiers. The overall experimental results demonstrate that the proposed disposable all-printed biosensor is applicable for the rapid detection and classification of pathogens.

A flat-panel-shaped hybrid piezo/triboelectric nanogenerator for ambient energy harvesting.

Recently, many researchers have been paying attention to nanogenerators (NGs) as energy sources for self-powered mirco-nano systems, and studying how to achieve their higher power generation. Hence, we propose a hybrid-type NG for harvesting both the piezoelectric and triboelectric effect simultaneously. In the proposed hybrid NG, the piezoelectric NG (PNG) and triboelectric NG (TENG) are fabricated using polydimethylsiloxane (PDMS) and perovskite zinc stannite (ZnSnO3) nanocubes with a high charge polarization of 59 uC cm-2 composite (PDMS + ZnSnO3) and UV surface-treated PDMS, respectively. To effectively combine a high output current of PNG and a high voltage of TENG, these two NGs are stacked upon each other, and separated by sponge spacers providing a uniform air gap for the triboelectric effect. In particular, this fabricated structure has a low Young's modulus for piezoelectricity. The proposed hybrid NG device effectively achieves a combined peak voltage of 300 V on an open circuit, a power density of 10.41 mW cm-2 at 1 MΩ load, and a maximum short circuit current density of 16 mA cm-2 at 50 Ω load. It is feasible that the proposed NG can be utilized as a source for various self-powered systems.

Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling.

Modeling the distributions of species, especially of invasive species in non-native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species-environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species' native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our 'best' model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium. However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed.

Growth and yield of rice as affected by transplanting dates and seedlings per hill under high temperature of Dera Ismail Khan, Pakistan.

Studies were initiated for two consecutive years to find out the effect of time of transplanting and seedlings hill(-1) on the productivity of rice in Dera Ismail Khan district of North West Frontier Province (NWFP), Pakistan. The experiment was laid out in a randomized complete block design with split plot arrangements. Main plots consisted of four transplanting dates viz. 20th and 27th of June and 4th and 11th of July while sub-plots contained 1, 2, 3 or 4 seedlings hill(-1). Among transplanting dates, June 20th planted crop gave highest paddy yield and net return with 1 seedling hill(-1). It explains that the use of more seedlings hill(-1) not only adds to cost but is also a mere wastage of natural resources. Based on research findings, we conclude that the use of 1 seedling hill(-1) is most appropriate for timely sowing otherwise 4 seedlings hill(-1) should be used to compensate for the yield gap in late transplanted rice.