First Reported Case of Lorazepam-Assisted Interview in a Young Indian Female Presenting with Dissociative Identity Disorder and Improvement in Symptoms after the Interview

Dissociative identity disorder (DID) is one of the most fascinating disorders in psychiatry. The arduous search to reveal the obscurity of this disorder has led to colossal research in this area over the years. Although drug-assisted interviews are not widely used, they may be beneficial for some patients that do not respond to conventional treatments such as supportive psychotherapy or psychopharmacotherapy. Drug-assisted interviews facilitate recall of memories in promoting integration of dissociative information. We report a case of a 16-year-old female with dissociative identity disorder (DID) that was treated with lorazepam-assisted interview and there was rapid improvement in symptoms after the interview

TCEP:Adapting to Dynamic User Environments by Enabling Transitions between Operator Placement Mechanisms

Operator placement has a profound impact on the performance of a distributed complex event processing system (DCEP). Since the behavior of a placement mechanism strongly depends on its environment; a single placement mechanism is often not enough to fulfill stringent performance requirements under environmental changes. In this paper, we show how DCEP can benefit from the adaptive use of multiple placement mechanisms. We propose Tcep, a DCEP system to integrate multiple placement mechanisms. By enabling transitions, Tcep can seamlessly exchange distinct operator mechanisms at runtime. We make two main contributions that are highly important for a cost-efficient transition: i) a transition strategy for efficiently scheduling state migrations and ii) a lightweight learning algorithm to adaptively select an appropriate placement mechanism as a consequence of a transition. Our evaluations for important decentralized placement mechanisms in the context of an IoT scenario show that transitions can better fulfill QoS demands in a dynamic environment. Thereby efficient scheduling of state migrations can help to faster complete transitions by up to 94 %

Accelerated Dynamic MRI Using Kernel-Based Low Rank Constraint

We present a novel reconstruction method for dynamic MR images from highly under-sampled k-space measurements. The reconstruction problem is posed as spectrally regularized matrix recovery problem, where kernel-based low rank constraint is employed to effectively utilize the non-linear correlations between the images in the dynamic sequence. Unlike other kernel-based methods, we use a single-step regularized reconstruction approach to simultaneously learn the kernel basis functions and the weights. The objective function is optimized using variable splitting and alternating direction method of multipliers. The framework can seamlessly handle additional sparsity constraints such as spatio-temporal total variation. The algorithm performance is evaluated on a numerical phantom and in vivo data sets and it shows significant improvement over the comparison methods

A distance vector hop-based secure and robust localization algorithm for wireless sensor networks

Location information of sensor nodes in a wireless sensor network is important. The sensor nodes are usually required to ascertain their positions so that the data collected by these nodes can be labeled with this information. On the other hand, certain attacks on wireless sensor networks lead to the incorrect estimation of sensor node positions. In such situations, when the location information is not correct, the data may be labeled with wrong location information that may subvert the desired operation of the wireless sensor network. In this work, we formulate and propose a distance vector hop-based algorithm to provide secure and robust localization in the presence of malicious sensor nodes that result in incorrect position estimation and jeopardize the wireless sensor network operation. The algorithm uses cryptography to ensure secure and robust operation in the presence of adversaries in the sensor network. As a result of the countermeasures, the attacks are neutralized and the sensor nodes are able to estimate their positions as desired. Our secure localization algorithm provides a defense against various types of security attacks, such as selective forwarding, wormhole, Sybil, tampering, and traffic replay, compared with other algorithms which provide security against only one or two types. Simulation experiments are performed to evaluate the performance of the proposed method, and the results indicate that our secure localization algorithm achieves the design objectives successfully. Performance of the proposed method is also compared with the performance of basic distance vector hop algorithm and two secure algorithms based on distance vector hop localization. The results reveal that our proposed secure localization algorithm outperforms the compared algorithms in the presence of multiple attacks by malicious nodes

Adaptive Multi-Cost Routing Protocol to Enhance Lifetime for Wireless Body Area Network

Wireless Body Area Network (WBAN) technologies are emerging with extensive applications in several domains. Health is a fascinating domain of WBAN for smart monitoring of a patient's condition. An important factor to consider in WBAN is a node's lifetime. Improving the lifetime of nodes is critical to address many issues, such as utility and reliability. Existing routing protocols have addressed the energy conservation problem but considered only a few parameters, thus affecting their performance. Moreover, most of the existing schemes did not consider traffic prioritization which is critical in WBANs. In this paper, an adaptive multi-cost routing protocol is proposed with a multi-objective cost function considering minimum distance from sink, temperature of sensor nodes, priority of sensed data, and maximum residual energy on sensor nodes. The performance of the proposed protocol is compared with the existing schemes for the parameters: network lifetime, stability period, throughput, energy consumption, and path loss. It is evident from the obtained results that the proposed protocol improves network lifetime and stability period by 30% and 15%, respectively, as well as outperforms the existing protocols in terms of throughput, energy consumption, and path loss

Mitigation of Power Losses and Enhancement in Voltage Profile by Optimal Placement of Capacitor Banks With Particle Swarm Optimization in Radial Distribution Networks

The prime purpose of placing a capaci- tor bank in a power system is to provide reactive power, reduce power losses, and enhances voltage profile. The main challenge is to determine the optimum capacitor position and size that reduces both system power losses and the overall cost of the sys- tem with rigid constraints. For this purpose, different optimization techniques are used, for example Particle Swarm Optimization (PSO) which converges the com- plex non-linear problem in a systematic and method- ological way to find the best optimal solution. In this paper, the standard IEEE 33-bus and 69-bus systems are used to find the optimum location and size of the capacitors bank. These power networks are simu- lated in Siemens PSS®E software. For the optimum solution of capacitor banks, the PSO algorithm is used. The PSO fitness function is modelled in such a way which contains the high average bus voltage, the small size of capacitor banks, and low power losses. The fitness function used is a weighted type to reduce the computation time and multi-objective function complexity

TCEP: Adapting to Dynamic User Environments by Enabling Transitions between Operator Placement Mechanisms

Operator placement has a profound impact on the performance of a distributed complex event processing system (DCEP). Since the behavior of a placement mechanism strongly depends on its environment; a single placement mechanism is often not enough to fulfill stringent performance requirements under environmental changes. In this paper, we show how DCEP can benefit from the adaptive use of multiple placement mechanisms. We propose Tcep, a DCEP system to integrate multiple placement mechanisms. By enabling transitions, Tcep can seamlessly exchange distinct operator mechanisms at runtime. We make two main contributions that are highly important for a cost-efficient transition: i) a transition strategy for efficiently scheduling state migrations and ii) a lightweight learning algorithm to adaptively select an appropriate placement mechanism as a consequence of a transition. Our evaluations for important decentralized placement mechanisms in the context of an IoT scenario show that transitions can better fulfill QoS demands in a dynamic environment. Thereby, efficient scheduling of state migrations can help to faster complete transitions by up to 94 %

Performance Analysis of a Parabolic trough Concentrated Solar Power Technology in Pakistan

International audienc

A biallelic variant in IQCE predisposed to cause non-syndromic post-axial polydactyly type A

Background: Polydactyly or hexadactyly is a familiar limb defect that either occurs as an isolated entity (non-syndromic) or is associated with severe (syndromic) morphological phenotypes. Generally, it appears due to a defect in the anteroposterior patterning during limb development. Methods: Here, we present a proband having non-syndromic post-axial polydactyly (PAP) evaluated using whole exome sequencing followed by Sanger sequencing. Furthermore, 3D protein modeling was executed for the normal and mutated IQ domain-containing protein E (IQCE) gene. Results: WES analysis revealed an already reported bi-allelic variant (c.395-1 G>A) in the IQCE gene, previously associated with PAP 7. Furthermore, 3D modeling revealed significant fluctuations in the IQCE protein secondary structure, thus affecting downstream signaling. Conclusion: The work presented validated the significant role of the IQCE gene in the development and patterning of human limbs. [JBCGenetics 2023; 6(1.000): 29-35