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Cell type classification and isolation according to imaging and spatial characteristics, beyond traditional fluorescently labeled biomarkers, enable the development of new biological insight and establishment of connections between phenotypical, morphological, and genomic cell information in normal and diseased states. Here we demonstrate a 2D image-guided cell sorter and a 3D imaging flow cytometer using fast scanning laser excitation sources. Both systems feature a cameraless design, which reconstructs cell images from the temporal readout of photomultiplier tubes.

A motivating and fun activity for students in introductory chemistry has been designed to increase familiarity with the chemical elements, symbols, and atomic numbers in the periodic table. This activity, Elemental Knock-Out, is a table tennis game, and the gameplay is adapted from a box grid baseball game. Playing in teams for fun and enjoyment, students work cooperatively with others to compete against an opposing team. The game is designed for first-year undergraduate students. The cost of one set of game materials is less than $50. The average time required to complete one game, i.e., to become familiar with the chemical elements and atomic numbers, is about 120 min for a class of 60 students. This game was implemented with 118 students including different grade classes. The results were interpreted through poll and quiz before and after the activity. The results of the study revealed that most of the students had positive impressions of the game and considered it to be a fun way of interacting with t...

Classification of cell types and isolation of targeted cells according to their imaging and spatial characteristics, beyond traditional fluorescently labeled biomarkers, enable the development of new biological insight and establishment of connections between phenotypical and morphological, and genomic cell information in normal and diseased states. Here, we demonstrate a microfluidic flow cytometer cell sorter that uses fast scanning laser excitation sources and photomultiplier tubes (PMTs), coupled with real-time image processing, to image and sort cells based on user-defined spatial features. Dozens of features, including label-free characteristics such as size, shape, scattering pattern, morphology, as well as the spatial distribution of fluorescently labeled biomarkers, greatly expand the available information space in cell analysis. The use of a disposable microfluidic cartridge that is compatible with the imaging system contributes to size reduction and lowered risk of cross contamination. The so-called cameraless design that uses PMTs to replace CCD makes the system more compatible with conventional fluorescence-activated cell sorters and user friendly, while enjoying the sensitivity and benefits of PMTs. The cell image features can be directly extracted from the temporal waveforms or from the reconstructed cell images via temporal–spatial transformation.

Schedule delays commonly occur in construction projects and often result in delay claims. Several studies have proposed different schedule delay analysis methodologies. By using as-planned and as-built schedules, most previous studies have concentrated on calculating the impact of identified delay events on project duration but have neglected to connect impact calculation from detailed delay evidence in their analyses. Lost productivity, which is a primary cause of schedule delays, entails the completion of work at less than the planned rate of production; it is usually experienced by contractors. To solve analysis problem of schedule delays associated with lost productivity, this study proposes a delay analysis method (the LOPE method) that integrates a lost productivity calculation approach and a well-known schedule delay analysis method, the collapsed as-built method. As demonstrated through a simplified case study, the proposed method is beneficial for calculating the impacts of schedule delays caused by lost productivity.

An all-inkjet-printed organic thin film transistor (OTFT) with a double-layer dielectric structure is proposed and implemented in this study. By using the double-layer structure with different dielectric materials (i.e., polyvinylphenol with poly(vinylidene fluoride-co-hexafluoropropylene)), the threshold-voltage of OTFT can be adjusted. The threshold-voltage shift can be controlled by changing the composition of dielectric layers. That is, an enhancement-mode OTFT can be converted to a depletion-mode OTFT by selectively printing additional dielectric layers to form a high-k/low-k double-layer structure. The printed OTFT has a carrier mobility of 5.0 × 10 − 3 cm 2 /V-s. The threshold-voltages of the OTFTs ranged between − 13 V and 10 V. This study demonstrates an additional design parameter for organic electronics manufactured using inkjet printing technology.

A dependent group contingency strategy called Fair Play Game was applied to promote increase in number of steps during physical education classes for sixth-grade students. Results from a multiple baseline design across three classes showed that the mean number of steps for baseline vs. intervention were: Class 1: 43 vs. 64 steps/minute; Class 2: 49 vs. 81 steps/minute; Class 3: 50 vs. 87 steps/minute. Visual inspection of the graphs showed that Class 1 had an upward trend of number of steps (baseline vs. intervention) without a change in level. Classes 2 and 3 demonstrated clearer change in level of number of steps between these two phases. Social validity data showed that students increased their engagement in class and Fair Play Game is a feasible and acceptable strategy. Therefore, it can be concluded that Fair Play Game appeared to be associated with students' increase in active behaviours in physical education lessons.

In view of water pollutants becoming more complex, both anionic and cationic pollutants need to be removed. The multi-pollutants simultaneous removal is paid more and more attention. Hence, development composite materials for treatment complex wastewater are the aim of this study. In this research, iron–nickel nanoparticles deposited onto aluminum oxide (α-Al2O3) and carbon nanotubes (CNTs) to form nanocomposite materials Fe–Ni/Al2O3 and Fe–Ni/CNTs, respectively, were used as adsorbents. The adsorption capacities of Fe–Ni/Al2O3 and Fe–Ni/CNTs for AO7, HSeO, and Pb2+ were observed to be 5.46, 8.28, 27.02, and 25.6 mg/g, 15.29 and 17.12 mg/g, separately. The composite materials with negative charges were superior in adsorption of anionic pollutants. Using orthogonal experimental design and analysis of variance to co-treat dye AO7, HSeO and Pb2+ in aqueous solutions, seven testing factors were included: (1) adsorbent types, (2) amount of iron, (3) solution pHs, (4) AO7 concentrations, (5) Pb2+ concentrations, (6) HSeO concentrations and (7) reaction time. The experimental results showed that the removal of complex pollutants AO7, HSeO, and Pb2+ on Fe–Ni/CNTs could reach up to 90% in the optimal treatment conditions. When using Fe–Ni/CNTs as the adsorbent, the sorption isothermals were well fitted in the Freundlich isotherm, and R2 could reach up to 0.98.

Organoboronic acid derivatives are well-established intermediates for the preparation of alcohols and amines, and in the formation of C–C bonds via different reactions, including homologations, carbonyl allylboration, or transition-metal-catalyzed cross-coupling chemistry. In the past decade, there has been great interest in the development of catalytic enantioselective methods for the preparation of chiral, optically enriched organoboronates as precursors of enantioenriched compounds. While the mainstream strategy remains the late-stage borylation of organic functional groups, our group has focused on an alternate strategy focused on modification of boron-containing substrates. In this way, acyclic and cyclic secondary alkyl- and allyl-boronates were prepared through catalytic enantioselective processes such as [4 + 2] cycloadditions, isomerizations, allylic substitutions, and conjugate additions. The resulting optically enriched boronates have been successfully utilized in the syntheses of complex natural products and drugs. One remaining challenge in the chemistry of secondary alkylboronate derivatives is their cross-coupling, especially with control of stereoselectivity. In this regard, our recent approach featured the conjugate asymmetric borylation of β-boronyl acrylates, providing the first enantioselective preparation of highly optically enriched 1,1-diboronyl derivatives. The chirality of these geminal diboron compounds is conferred through the use of two distinct boronate adducts, which can be coupled chemo- and stereoselectively with a variety of aryl and alkenyl halides under palladium catalysis.

To enhance the carrier mobility of all-inkjet-printed organic thin film transistors, we fabricated devices that incorporated poly(3-hexylthiophene) (P3HT) and carbon nanoparticles (CNPs). The fabricated devices had an on/off ratio of 104, which is one order less than that of pristine organic thin-film transistors (OTFTs). The maximum carrier mobility as high as 0.053 cm2/V-s was achieved for a CNP/P3HT weight–weight ratio of 7/100. This degree of mobility is 10 times greater than average mobility of pristine P3HT-OTFTs. X-ray diffraction and scanning electron microscopy images reveal that the carrier mobility was enhanced by reducing the injection barrier and enhancing the carrier injection. This work demonstrates the feasibility of all-inkjet-printed OTFT technology.

Gold (I) complexes generated from a mixture of gold and silver salts were found to be highly reactive for the cycloisomerization reactions of boronated enynes. Both alkynyl pinacol boronates and alkenyl pinacol boronates were tolerated, affording products in moderate to high yields. Interestingly, the ratio of the different endo- and exo-products was heavily dependent on the position of the boronate functionality. Further applications including Suzuki–Miyaura cross coupling and oxidation reactions could be carried out, affording a variety of synthetically useful products.

With the fast increase in Web activities, Web data mining has recently become an important research topic and is receiving a significant amount of interest from both academic and industrial environments. While existing methods are efficient for the mining of frequent path traversal patterns from the access information contained in a log file, these approaches are likely to over evaluate associations. Explicitly, most previous studies of mining path traversal patterns are based on the model of a uniform support threshold, where a single support threshold is used to determine frequent traversal patterns without taking into consideration such important factors as the length of a pattern, the positions of Web pages, and the importance of a particular pattern, etc. As a result, a low support threshold will lead to lots of uninteresting patterns derived whereas a high support threshold may cause some interesting patterns with lower supports to be ignored. In view of this, this paper broadens the horizon of frequent path traversal pattern mining by introducing a flexible model of mining Web traversal patterns with dynamic thresholds. Specifically, we study and apply the Markov chain model to provide the determination of support threshold of Web documents; and further, by properly employing some effective techniques devised for joining reference sequences, the proposed algorithm dynamic threshold miner (DTM) not only possesses the capability of mining with dynamic thresholds, but also significantly improves the execution efficiency as well as contributes to the incremental mining of Web traversal patterns. Performance of algorithm DTM and the extension of existing methods is comparatively analyzed with synthetic and real Web logs. It is shown that the option of algorithm DTM is very advantageous in reducing the number of unnecessary rules produced and leads to prominent performance improvement.

Substrate (I) which bears a Weinreb amide undergoes a direct coupling of the Bpin moiety with inversion of the stereochemistry.

A method has been developed for the chemo- and stereoselective Suzuki-Miyaura cross-coupling of optically enriched gem-diboronyl compounds with various aryl bromides. Experimental evidence suggests that the Lewis acidity of the second boron group in these substrates plays a significant role in facilitating these otherwise challenging cross-coupling processes. β-Diboronyl esters may be successfully cross-coupled in excellent yield and enantiomeric excess with prior conversion of the pinacol boronate to the corresponding trifluoroborate salt. In contrast, a substrate bearing a Weinreb amide can undergo direct coupling of the Bpin moiety, likely due to the stronger coordination of the more basic amide carbonyl group. The resulting optically enriched secondary boronate may be used in a second enantioselective cross-coupling to afford pharmaceutically relevant diarylmethane products. The use of a Weinreb amide substrate allows for facile postcoupling modification, as demonstrated by a transformation to the corresponding ketone.

Recently, several important database applications have called for the design of efficient techniques for incremental mining of association rules. In response to this need, we explore in this paper an effective sliding-window filtering (abbreviatedly as SWF) algorithm for incremental mining of association rules. In essence, by partitioning a transaction database into several partitions, algorithm SWF employs a filtering threshold in each partition to deal with the candidate itemset generation. Under SWF, the cumulative information of mining previous partitions is selectively carried over toward the generation of candidate itemsets for the subsequent partitions. Algorithm SWF not only significantly reduces I/O and CPU cost by the concepts of cumulative filtering and scan reduction techniques but also effectively controls memory utilization by the technique of sliding-window partition. More importantly, algorithm SWF is particularly powerful for efficient incremental mining for an ongoing time-variant transaction database. By utilizing proper scan reduction techniques, only one scan of the incremented dataset is needed by algorithm SWF. The I/O cost of SWF is, in orders of magnitude, smaller than those required by prior methods, thus resolving the performance bottleneck. Extensive experimental studies are performed to evaluate performance of algorithm SWF. Sensitivity analysis of various parameters is conducted to provide many insights into algorithm SWF. It is noted that the improvement achieved by algorithm SWF is even more prominent as the incremented portion of the dataset increases and also as the size of the database increases.

We explore a new problem of mining general temporal association rules in publication databases. In essence, a publication database is a set of transactions where each transaction T is a set of items of which each item contains an individual exhibition period. The current model of association rule mining is not able to handle the publication database due to the following fundamental problems, i.e., 1) lack of consideration of the exhibition period of each individual item and 2) lack of an equitable support counting basis for each item. To remedy this, we propose an innovative algorithm progressive-partition-miner (abbreviated as PPM) to discover general temporal association rules in a publication database. The basic idea of PPM is to first partition the publication database in light of exhibition periods of items and then progressively accumulate the occurrence count of each candidate 2-itemset based on the intrinsic partitioning characteristics. Algorithm PPM is also designed to employ a filtering threshold in each partition to early prune out those cumulatively infrequent 2-itemsets. The feature that the number of candidate 2-itemsets generated by PPM is very close to the number of frequent 2-itemsets allows us to employ the scan reduction technique to effectively reduce the number of database scans. Explicitly, the execution time of PPM is, in orders of magnitude, smaller than those required by other competitive schemes that are directly extended from existing methods. The correctness of PPM is proven and some of its theoretical properties are derived. Sensitivity analysis of various parameters is conducted to provide many insights into Algorithm PPM.

The query processing in a mobile computing environment involves join processing among different sites which include static servers and mobile computers. Because of the presence of asymmetric features in a mobile computing environment, the conventional query processing for a distributed database cannot be directly applied to a mobile computing system. In this paper, we first explore some unique features of a mobile environment and then, in light of these features, devise query processing methods for both join and query processing. Remote mobile joins are said to be effectual if they are, when being interleaved into a join sequence, able to reduce the amount of data transmission cost required for distributed mobile query processing. Since mobile relations are employed as reducers in our proposed query processing cost model, more mobile joins in the query processing lead to less data transmitted through the network. With proper scheduling, interleaving effectual remote mobile joins into a query scheduling can significantly reduce the total amount of data transmission among different sites. A simulator is developed to evaluate the performance of algorithms devised. Our results show that the approach of interleaving the processing of distributed mobile queries with effectual remote mobile joins is not only efficient, but also effective in reducing the total amount of data transmission cost required to process distributed mobile queries.

A Solar-Powered Sensor Module (SPSM) that uses low-cost capacitors as energy buffers to power wireless sensor motes was investigated. Compared to batteries or super capacitors, SPSM is particularly suitable for light-weight tasks since it buffers limited energy and powers up periodically. With our method, the energy charging time can be shortened to about 100 ms for a maximum power point tracking component, and the current of the output regulator can reach 71% efficiency.

To improve the field-effect mobility of all-inkjet-printed organic thin film transistors (OTFTs), a composite material consisted of carbon nanoparticles (CNPs) and poly(3-hexylthiophene) (P3HT) was reported by using homemade inkjet-printing system. These all-inkjet-printed composite OTFTs represented superior characteristics compared to the all-inkjet-printed pristine P3HT OTFTs. To investigate the enhancement mechanism of the blended materials, the percolation model was established and experimentally verified to illustrate the enhancement of the electrical properties with different blending concentrations. In addition, experimental results of OTFT contact resistances showed that both contact resistance and channel resistance were halved. At the same time, X-ray diffraction measurements, Fourier transform infrared spectra, ultraviolet-visible light, and photoluminescence spectra were also accomplished to clarify the material blending effects. Therefore, this study demonstrates the potential and guideline of carbon-based nanocomposite materials in all-inkjet-printed organic electronics.

Organoboronic acid derivatives are well-established intermediates for the prepara- tion of alcohols and amines, and in the formation of C-C bonds via different reactions, including homologations, carbonyl allylboration, or transition-metal-catalyzed cross-cou- pling chemistry. In the past decade, there has been great interest in the development of cat- alytic enantioselective methods for the preparation of chiral, optically enriched organoboronates as precursors of enantioenriched compounds. While the mainstream strat- egy remains the late-stage borylation of organic functional groups, our group has focused on an alternate strategy focused on modification of boron-containing substrates. In this way, acyclic and cyclic secondary alkyl - and allyl-boronates were prepared through catalytic enantio selective processes such as (4 + 2) cycloadditions, isomerizations, allylic substitu- tions, and conjugate additions. The resulting optically enriched boronates have been suc- cessfully utilized in the syntheses of complex natural products and drugs. One remaining challenge in the chemistry of secondary alkylboronate derivatives is their cross-coupling, especially with control of stereoselectivity. In this regard, our recent approach featured the conjugate asymmetric borylation of β-boronyl acrylates, providing the first enantioselective preparation of highly optically enriched 1,1-diboronyl derivatives. The chirality of these geminal diboron compounds is conferred through the use of two distinct boronate adducts, which can be coupled chemo- and stereoselectively with a variety of aryl and alkenyl halides under palladium catalysis.

The planar 1,8-diaminonaphthalene moiety acts as a superior boron masking group over the bulky pinacol group.

In this paper, a low cost and low power consumption humidity sensor was developed by blending SiO 2 nano-particles blending with PEDOT conductive polymers. The developed sensing material was fabricated by inkjet-printing technology on silicon substrate. Compared with pristine PEDOT:PSS materials, the adding of SiO 2 nano-particles improves the sensitivity of humidity with a factor of 2. The time response of the developed sensing material was also examined to evaluate its sensing stabilities. At the same time, the sensor selectivity to humidity, CO2, and NO was also experimentally tested. This work developed a promising inkjet-printable humidity sensing materials for various applications.

A new methodology has been developed for the stereoselective preparation of β-aryl-β-boronyl α,β-unsaturated esters via Heck coupling, and their subsequent copper(I)-catalyzed enantioselective conjugate reduction. Various chiral secondary boronate derivatives can be accessed in excellent yields and good to high levels of enantioselectivity through the efficient copper-catalyzed process using polymethylhydrosiloxane (PMHS) as the hydride source.

Schedule delays commonly appear in construction projects and result in delay claim progressively. Several studies have proposed various schedule delay analysis methodologies; however, most of the studies focus on the analysis of surface data (as-planned and as-built schedules), few of them on evaluating the effects of root causes, such as the problem of lost productivity. Lost productivity, one essential delay cause, is usually experienced by a contractor while accomplishing its works less than planned rate of production. For analyzing the situations of schedule impacts caused by lost productivity, this study discusses a case of delay analysis with lost productivity in Taiwan. Through the study case, this study has proposed an approach to calculate schedule impact from lost productivity. The study results will be a basis for developing a comprehensive delay analysis method considering lost productivity.

The simplicity, efficiency and generality of the transition-metal-catalysed Suzuki-Miyaura cross-coupling reaction has led to its application in the preparation of a wide variety of organic compounds. Cross-coupling of alkylboron derivatives, however, remains a major challenge, in particular with regard to stereochemical control. Here, we describe the preparation and reaction of highly optically enriched 1,1-diboron compounds. A catalytic asymmetric conjugate borylation of β-boronylacrylates provided geminal diboronate products that feature two distinct boronyl units, in 99% enantiomeric excess. Chemoselective cross-coupling of one-boronyl unit, a trifluoroborate salt, occurred stereospecifically via inversion of its configuration to generate enantioenriched benzylic or allylic boronates. The difficult transmetallation in the Suzuki-Miyaura catalytic reaction cycle is believed to be facilitated by a stabilization effect from the second boronyl unit, and internal coordination by the oxygen of the proximal carboxyester. We also explored subsequent functionalization of the second boronyl unit.

Poly(3-hexylthiophene), P3HT, has been widely used in organic electronics as a semiconductor material. It suffers from the low carrier mobility characteristics. This limits P3HT to be employed in applications. Therefore, the blending semiconductor material, carbon nanoparticle (CNP), and P3HT, are developed and examined by inkjet-printing organic field-effect transistor technology in this work. The effective carrier mobility of fabricated OFETs can be enhanced by 8 folds with adding CNP and using O2plasma treatment. At the same time, the transconductance of fabricated OFETs is also raised by 5 folds. Based on the observations of SEM, XRD, and FTIR, these improvements are contributed to the local field induced by the formation of CNP/P3HT complexes. This observation presents an insight of the development in organic semiconductor materials. Moreover, this work also offers a low-cost and effective semiconductor material for inkjet-printing technology in the development of organic electronics.

There is a growing interest in the development of new methods to prepare chiral organoboronate derivatives in optically pure form. An efficient copper-catalyzed enantioselective conjugate addition methodology using Grignard reagents and 3-boronyl acrylate derivatives was optimized for the preparation of chiral alkylboronate products in high yields and up to 98% ee. The resulting 1,8-diaminonaphthalene adducts can be transformed into the corresponding boronic acid, pinacol boronate, and trifluoroborate salt. This method extends the realm of chemical reactions compatible with useful boron-containing substrates.

Schedule delays commonly appear in construction projects and result in delay claim progressively. Several studies have proposed various schedule delay analysis methodologies, however, most of the studies focused on the analysis of surface data (as-planned and as-built schedules), few of them on evaluating the effects of root causes, such as lost productivity. Loss of productivity is usually experienced by a contractor while accomplishing its works less than planned rate of production. Based on the literature review on lost productivity, this study further evaluated delay analysis methodologies, professional project management software and commercial delay analysis software to identify the capabilities of those methodologies and systems in dealing with the problem of lost productivity. Research results show that evaluated delay analysis methodologies, professional project management software and commercial delay analysis software cannot deal with the problem of lost productivity appropriately. That is, developing a comprehensive delay analysis method considering lost productivity is required.

Through density functional calculation and NMR spectroscopy, an unexpected bonding interaction between d(xy) and axial cyanides is revealed to account for the lower shielding of axial cyanide of ruffled [Fe(TRP)(CN)(2)](-) complexes with the contribution of the unusual low-spin electronic structure (d(xz)d(yz))(4)(d(xy))(1).

With the fast increase in Web activities, Web data mining has recently become an important research topic. However, most previous studies of mining path traversal patterns are based on the model of a uniform support threshold without taking into consideration such important factors as the length of a pattern, the positions of Web pages, and the importance of a particular pattern, etc. In view of this, we study and apply the Markov chain model to provide the determination of support threshold of Web documents. Furthermore, by properly employing some techniques devised for joining reference sequences, a new mining procedure of Web traversal patterns is proposed in this paper.

In this paper, we explore a new problem of mining general temporal association rules in publication databases. In essence, a publication database is a set of transactions where each transaction T is a set of items, each containing an individual exhibition period. The current model of association rule mining is not able to handle a publication database due to the following fundamental problems: (1) lack of consideration of the exhibition period of each individual item; and (2) lack of an equitable support counting basis for each item. To remedy this, we propose an innovative algorithm, progressive-partition-miner (PPM), to discover general temporal association rules in a publication database. The basic idea of PPM is to first partition the publication database into exhibition periods of items and then progressively accumulate the occurrence count of each candidate 2-itemset based on the intrinsic partitioning characteristics. PPM is also designed to employ a filtering threshold in each partition to prune out those cumulatively infrequent 2-itemsets at an early stage. Explicitly, the execution time of PPM is, in orders of magnitude, smaller than those required by schemes which are directly extended from existing methods.

We introduce the concept of network graph for distributed query processing. Semijoins and joins are termed contributive replicated semijoins and contributive replicated joins, respectively, when they are interleaved into a join sequence to reduce the amount of data transmission cost required in a network with replicated relations. Our solution procedure consists of three consecutive steps, namely relation selection, join sequence scheduling and merge processing. A simulator is developed to evaluate the performance of algorithms devised. Our results show that the approach of interleaving a join sequence with contributive replicated semijoins/joins is not only efficient in its execution but also effective in reducing the total amount of data transmission cost required to process distributed queries.

In this paper, we broaden the horizon of traditional rule mining by introducing a new framework of causality rule mining in a distributed chain store database. Specifically, the causality rule explored in this paper consists of a sequence of triggering events and a set of consequential events, and is designed with the capability of mining non-sequential, inter-transaction information. Hence, the causality rule mining provides a very general framework for rule derivation. Note, however, that the procedure of causality rule mining is very costly particularly in the presence of a huge number of candidate sets and a distributed database, and in our opinion, cannot be dealt with by direct extensions from existing rule mining methods. Consequently, we devise in this paper a series of level matching algorithms, including Level Matching (abbreviatedly as LM), Level Matching with Selective Scan (abbreviatedly as LMS), and Distributed Level Matching (abbreviatedly as Distibuted LM), to minimize the computing cost needed for the distributed data mining of causality rules. In addition, the phenomena of time window constraints are also taken into consideration for the development of our algorithms. As a result of properly employing the technologies of level matching and selective scan, the proposed algorithms present good efficiency and scalability in the mining of local and global causality rules. Scale-up experiments show that the proposed algorithms scale well with the number of sites and the number of customer transactions.Index Terms: knowledge discovery, distributed data mining causality rules, triggering events, consequential events

The Fair Play Game is a group contingency strategy in which students within a group can work together toward a final goal. This strategy gives teachers the flexibility to choose behaviors or skills...